US20140324427A1 - System and dialog manager developed using modular spoken-dialog components - Google Patents
System and dialog manager developed using modular spoken-dialog components Download PDFInfo
- Publication number
- US20140324427A1 US20140324427A1 US14/261,549 US201414261549A US2014324427A1 US 20140324427 A1 US20140324427 A1 US 20140324427A1 US 201414261549 A US201414261549 A US 201414261549A US 2014324427 A1 US2014324427 A1 US 2014324427A1
- Authority
- US
- United States
- Prior art keywords
- subdialog
- application
- dialog
- available reusable
- context
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 claims abstract description 47
- 230000004044 response Effects 0.000 claims description 15
- 238000012360 testing method Methods 0.000 abstract description 7
- 230000007704 transition Effects 0.000 description 81
- 230000009471 action Effects 0.000 description 56
- 238000011161 development Methods 0.000 description 19
- 230000018109 developmental process Effects 0.000 description 19
- 238000012790 confirmation Methods 0.000 description 17
- 230000008569 process Effects 0.000 description 17
- 230000003993 interaction Effects 0.000 description 10
- 238000012545 processing Methods 0.000 description 8
- 238000005352 clarification Methods 0.000 description 7
- 230000006870 function Effects 0.000 description 7
- 238000013459 approach Methods 0.000 description 6
- 230000008901 benefit Effects 0.000 description 4
- 230000004913 activation Effects 0.000 description 3
- 230000006399 behavior Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000012937 correction Methods 0.000 description 3
- 230000007246 mechanism Effects 0.000 description 3
- 238000012546 transfer Methods 0.000 description 3
- 230000003190 augmentative effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000005538 encapsulation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 235000006719 Cassia obtusifolia Nutrition 0.000 description 1
- 235000014552 Cassia tora Nutrition 0.000 description 1
- 244000201986 Cassia tora Species 0.000 description 1
- 230000009118 appropriate response Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000003416 augmentation Effects 0.000 description 1
- CVXBEEMKQHEXEN-UHFFFAOYSA-N carbaryl Chemical compound C1=CC=C2C(OC(=O)NC)=CC=CC2=C1 CVXBEEMKQHEXEN-UHFFFAOYSA-N 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000003012 network analysis Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012552 review Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000033772 system development Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
- G06F40/35—Discourse or dialogue representation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/205—Parsing
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L13/00—Speech synthesis; Text to speech systems
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/28—Constructional details of speech recognition systems
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/06—Transformation of speech into a non-audible representation, e.g. speech visualisation or speech processing for tactile aids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/191—Automatic line break hyphenation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/64—Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations
- H04M1/642—Automatic arrangements for answering calls; Automatic arrangements for recording messages for absent subscribers; Arrangements for recording conversations storing speech in digital form
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99931—Database or file accessing
- Y10S707/99932—Access augmentation or optimizing
Definitions
- the present invention relates to spoken dialog systems and more specifically to spoken dialog system and a dialog manager generated using a reusable dialog modular development approach.
- the present invention relates to spoken dialog systems and to the dialog manager module within such a system.
- the dialog manager controls the interactive strategy and flow once the semantic meaning of the user query is extracted.
- dialog manager continues to require highly-skilled and trained developers.
- the process of designing, developing, testing and deploying a spoken dialog service having an acceptably accurate dialog manager is costly and time-consuming.
- consumers further expect spoken dialog systems to handle more complex dialogs.
- higher costs and technical skills are required to develop more complex spoken dialog systems.
- An embodiment of the invention relates to a dialog manager for use within a spoken dialog service, the dialog manager generated according to a method comprising selecting a top level flow controller, selecting available reusable subdialogs for each application part below the top level flow controller, developing a subdialog for each application part not having an available subdialog and testing and deploying the spoken dialog service using the selected top level flow controller, selected reusable subdialogs and developed subdialogs.
- the top level flow controller, reusable subdialogs and developed subdialogs interact with each other independent of their decision model.
- dialog modules designed using rule-based decision models, recursive transition network (RTN) decision models or other decision models can all seamlessly communicate with each other without the need of the developer to design specific rules governing their interaction.
- functions that are dependent on or specific to a particular application such as presenting the top book sales associated a bookseller website, are not associated with the reusable subdialogs.
- the system returns a context shift indication and a destination state and returns control of the dialog to a top level controller or parent dialog. This enables the subdialogs to be reusable in different applications.
- inventions include but are not limited to (1) a modular subdialog having certain characteristics such that it can be selected and incorporated into a dialog manager below a top level flow controller.
- the modular subdialog can be called up by the top level flow controller to handle specific tasks and receive context data and return data to the top level flow control gathered from its interaction with the user as programmed; (2) a dialog manager generated according to the method set forth herein; (3) a computer readable medium storing program instructions or spoken dialog system components; and (4) a spoken dialog service having a dialog manager generated according to the process set forth herein.
- FIG. 1 illustrates the basic spoken dialog service
- FIG. 2 illustrates a flow controller in the context of a dialog manager
- FIG. 3 illustrates a dialog application top level flow controller and example subdialogs
- FIG. 4 illustrates a context shift associated with a flow controller
- FIG. 5A illustrates a reusable subdialog
- FIG. 5B illustrates an RTN reusable subdialog
- FIG. 6 illustrates a method aspect of the present invention
- FIG. 7 illustrates another method aspect of the invention associated with context shifts.
- FIG. 1 provides the basic modules that are used in a spoken dialog system 100 .
- a user 102 that is interacting with the system will speak a question or statement.
- An automatic speech recognition (ASR) module 104 will receive and process the sound from the speech.
- the speech is recognized and converted into text.
- AT&T's Watson ASR component is an example of such an ASR module.
- the text is transmitted to a spoken language understanding (SLU) module 106 (or natural language understanding (NLU) module) that determines the meaning of the speech, or determines the user's intent in the speech.
- SLU spoken language understanding
- NLU natural language understanding
- the NLU 106 uses its language models to interpret what the caller said.
- the NLU processes the spoken language input wherein the concepts and other extracted data are transmitted (preferably in XML code) from the NLU 106 to the DM application 108 along with a confidence score.
- the (DM) module 108 processes the received candidate intents or purposes of the user's speech and generates an appropriate response. In this regard, the DM 108 manages interaction with the caller, deciding how the system will respond to the caller.
- the DM engine 108 manages dialog with the caller by applying the compiled concepts returned from the NLU 106 to the logic models provided by the DM application 108 . This determines how the system interacts with a caller, within the context of an ongoing dialog.
- the substance of the response is transmitted to a spoken language generation component (SLG) 110 which generates words to be spoken to the caller 102 .
- the words are transmitted to a text-to-speech module 112 that synthesizes audible speech that the user 102 receives and hears.
- SSG spoken language generation component
- the SLG 110 either plays back pre-recorded prompts or real-time synthesized text-to-speech (TTS).
- TTS text-to-speech
- AT&T's Natural Voices® TTS engine provides an example of a TTS engine that is preferably used.
- Various types of data and rules 114 are employed in the training and run-time operation of each of these components.
- An example DM 108 component is the AT&T Florence DM engine and DM application development environment.
- the present invention relates to the DM component and will provide a novel approach to development and implementation of the DM module 108 .
- Other embodiments of the invention include a spoken dialog system having a DM that functions according to the disclosure here, a DM module independent of a spoken dialog service or other hardware or firmware, a computer-readable medium for controlling a computing device and various methods of practicing the invention. These various embodiments will be understood from the disclosure here.
- a spoken dialog system or dialog manager (as part of a spoken dialog system) will operate on a computing device such as the well-known computer system having a computer processor, volatile memory, a hard disc, a bus that transmits information from memory through the processor and to and from other computer components.
- a computing device such as the well-known computer system having a computer processor, volatile memory, a hard disc, a bus that transmits information from memory through the processor and to and from other computer components.
- the present invention is not limited to any specific computing structure but may be operable on any state-of-the-art device or network configuration.
- AT&T's Florence dialog management environment provides a complete framework for building and testing advanced natural language automated dialog applications.
- the core of Florence is its object-oriented framework of Java classes and standard dialog patterns. This serves as an immediate foundation for rapid development of dialog infrastructure with little or no additional programming.
- Florence offers tools to create a local development and test environment with many convenient and time-saving features to support dialog authoring.
- Florence also supplies a key runtime component for the VoiceTone Dialog Automation platform—the Florence Dialog Manager (DM) engine, an Enterprise Java Bean (EJB) on the VoiceTone/NLS J2EE application server.
- DM Florence Dialog Manager
- EJB Enterprise Java Bean
- the DM engine uses the logic built into the application's dialogs to manage interactions with end-users within the context of an on-going dialog.
- the DM application 108 will determine, for example, whether it is necessary to prompt the caller to get confirmation or clarification and whether the caller has provided sufficient information to establish an unambiguous course of action.
- the DM engine's output processor uses the DM application's dialog components and output template to prepare appropriate output. Output is most often formatted as VoiceXML code containing speech text prompts that will be used to generate a spoken response to the caller.
- a DM application 108 can also be configured to provide output in any XML-based language only replacing the appropriate output template.
- the DM application 108 may also generate output configured in other ways.
- plain text output is sufficient (as might be the case during application development/debugging)
- Florence's own simple output processor can be used in lieu of any output template.
- the DM's spoken language generator (SLG) 110 helps generate the system's response to the caller 102 .
- Output (such as VoiceXML code with speech text, for example) generated by the Florence output processor using a specific output template is run through the SLG 110 before it is sent to a text-to-speech (TTS) engine 112 .
- TTS text-to-speech
- both the DM and 108 the NLU 106 engines are preferably Enterprise Java Beans (EJBs) running on the NLS J2EE application server.
- the ASR and TTS engines communicate with the NLS server via a telephony server or some other communication means.
- EJBs is one way to implement the business logic and servlets or JSP pages are also alternative standard-based options.
- a DM application supplies dialog data and logical models pertaining to the kinds of tasks a user might be trying to perform and the dialog manager engine implements the call flow logic contained in the DM application to assist in completing those tasks.
- the dialog manager is also updating the dialog history (the record of the system's previous dialog interaction with a caller) by logging information representing an ongoing history of the dialog, including input received, decisions made, and output generated.
- Florence DM applications can be created and debugged in a local desktop development environment before they are deployed on the NLS J2EE application server.
- the Florence Toolkit includes a local copy of the XML schema, a local command line tool, and a local NLU server specifically for this purpose.
- DM applications that are to be deployed on the NLS server need to be tested with to NLS technology components residing on the J2EE server.
- FC Flow Controller
- a Flow Controller is the abstraction for pluggable dialog strategy modules.
- the dialog strategy model controls the flow of dialog when a user “converses” with the system.
- Dialog strategy implementations can be based on different types of dialog flow control logic models. Different algorithms can be implemented and made available to the DM engine without changing the basic interface. For example, customer care call routing systems are better described in terms of RTNs (Recursive Transition Networks). Complex knowledge-based tasks could be synthetically described by a variation of knowledge trees.
- Clarification FCs are basically decision trees, where dialog control passes from node to node along branches and are discussed in U.S.
- Plan-based dialogs are effectively defined by rules and constraints (rule-based).
- Florence FC provides a synthetic XML-based language to author the appropriate dialog strategy.
- Dialog strategy algorithms are encapsulated using object oriented paradigms. This allows dialog authors to write sub-dialogs with different algorithms, depending on the nature of the task and use them interchangeably exchanging variables through the local and global contexts.
- the disclosure below relates to RTN FCs.
- RTN FCs are finite state models, where a dialog control passes from one state to another and transitions between states have specific triggers. This decision system uses the notion of states connected by arcs. The path through the network is decided based on the conditions associated with the arcs. Each state is capable of calling a new subdialog. Additional types of FC implementations include a rules-based model. In this model, the author writes rules which are used to make decisions about how to interact with the user. The RTN FC is the preferred model for automated customer care services. All the FC family of dialog strategy algorithms, such as the RTN FC, the clarification FC, and the rule-based FC implementations support common dialog flow control features, such as context shifts, local context, actions, and subdialogs.
- the RTN FC is a state machine that uses states and transitions between states to control the dialog between a user and a DM application.
- states and transitions between states are often referred to as Augmented Transition Networks.
- Augmented Transition Networks are often referred to as Augmented Transition Networks. See, e.g., D. Bobrow and B. Fraser, “An Augmented State Transition Network Analysis Procedure”, Proceedings of the IJCAI , pages 557-567, Washington D.C., May 1969.
- the present document refers to RTNs only. If an application is using an RTN FC implementation in its currently active dialog, when the DM application receives user input, the DM engine applies the call logic defined in that RTN FC implementation to respond to the user in an appropriate manner.
- the RTN FC logic determines which state to advance to based on the input received from the caller. There may be associated sets of instructions that will be executed upon entering this state. (A state can have up to four or more instruction sets.) The transition from one state to another may also have an associated set of conditions that must be met in order to move to the next state or associated actions that are invoked when the transition occurs.
- Each RTN state is defined in the XML code of a dialog data file with a separate ⁇ state> element nested within the overall ⁇ states> element.
- the attributes of an RTN ⁇ state> element include name, subdialog and pause.
- the name attribute is the identifier of the state; it can be any string.
- the subdialog attribute is the name of the FC invoked as a subdialog. If this attribute is left out, the state will not create a subdialog.
- the pause attribute determines whether the RTN FC will pause. If this is set to true, the RTN controller will pause before exiting to get new user input. Note that if the state invokes a subdialog, it will not pause before the subdialog is invoked, but will pause after it returns control. For example:
- the first stage relates to state entry instructions.
- the ⁇ enterstate> set of instructions is executed immediately when a transition delivers control to the state. If a state is reached by a context shift or a chronoshift, these instructions are not executed.
- a chronoshift denotes a request to back trace the dialog execution to a previous dialog turn. Chronoshifts typically also involved removing a previous dialog from the stack to give control to the previous dialog.
- the initial state of an RTN does not execute these instructions; however, if the RTN FC passes control to this state because it is the default state of the RTN FC, it will execute these instructions.
- the following is an example from a dialog file's XML code where a ⁇ set> element nested within an ⁇ enterstate> element includes entry instructions:
- the second stage relates to subdialog creation. If the state has a subdialog, then it is created at this stage.
- the following is an example of the syntax for a ⁇ state> element which calls a subdialog named InputSD:
- the third stage relates to subdialog entry instructions.
- the ⁇ entersubdialog> set of instructions is invoked when the state creates a subdialog.
- instructions in this stage affect both the dialog and the subdialog.
- the ⁇ set> instruction will retrieve values from the parent dialog and set values in the subdialog. This is useful for passing arguments to a subdialog before it executes.
- the invoked subdialog is pushed to the stop of the stack of dialog modules so that the invoked subdialog can manage the spoken dialog and interact with the user.
- the fourth stage relates to subdialog execution. If a subdialog was created in stage 2 (the subdialog creation stage), it is started in this stage. Input will be directed to the subdialog until it returns control to the dialog.
- the fifth stage relates to subdialog exit instructions.
- the ⁇ exitsubdialog> set of instructions is invoked when the subdialog returns control to the dialog.
- instructions in this stage affect both the dialog and the subdialog. This is useful for retrieving values from a subdialog when it is complete.
- the subdialog module is popped off the dialog module stack.
- the sixth stage relates to state exit instructions.
- the ⁇ exitstate> set of instructions is executed when a transition is used to exit a state or the RTN shifts control to the default state. These instructions are not executed if the state is left by a context shift or chronoshift, nor are they executed if this is a final state in this RTN.
- the six stages of a state and associated instruction sets are summarized in the table below. When a state has passed through all six of these stages (including those with no associated instructions) it will advance to a new state.
- Stage Instruction Set State Entry Use an ⁇ enterstate> element with a ⁇ set> element nested within it to identify a set of instructions associated with entering this state.
- Subdialog No instructions are used in Creation this stage, however, the subdialog attribute of the ⁇ state> element can be used to identify the subdialog being called.
- Subdialog Entry Use an ⁇ entersubdialog> element with a ⁇ set> element nested within it to identify a set of instructions associated with entering this subdialog.
- Subdialog No instructions are used in this stage.
- Execution Subdialog Exit Use an ⁇ exitsubdialog> element with a ⁇ set> element nested within it to identify a set of instructions associated with exiting this subdialog.
- State Exit Use an ⁇ exitstate> element with a ⁇ set> element nested within it to identify a set of instructions associated with exiting this state.
- Each RTN transition is defined in the XML code of the dialog file with a separate ⁇ transition> element nested within the overall ⁇ transitions> element.
- Each ⁇ transition> can have a set of conditions defined in a ⁇ conditions> element. This element must be evaluated to true in order for the transition to be traversable.
- Each ⁇ transition> can also have an element of type ⁇ actions>. This element contains the ⁇ action> elements which will be executed if this transition is selected. The following example comes from a sample application where callers order foreign language movies:
- Transitions can have conditions and actions associated with them, but not instructions. Transitions do not execute instructions; only states can affect the local context in an RTN FC.
- a transition can have an associated set of conditions which must all be fulfilled in order to be traversed—or, it can be marked as an “else transition”, which means it will be traversed if no other transition is eligible. Transitions with conditions that have been satisfied have priority over else transitions. If a transition has no conditions, it is treated as an else transition. If multiple transitions are eligible, which of the transitions will be selected as undefined—and which else transition will be selected if there is more than one is also undefined.
- a transition with two conditions is an example of a transition with two conditions:
- a transition can invoke any number of actions. This is an example of a transition with an action:
- the RTN FC is responsible for keeping track of action data.
- INTRO_PROMPT is a label that is used to look up the action data.
- other components of the RTN FC include: Local context, Context shifts, Subdialogs and Actions.
- Local context is a memory space for tracking stored values in an application. These values can be read and manipulated using conditions and instructions. Instructions modify the local context from RTN states.
- Context shifts are implemented with the ⁇ contextshifts> element. Each context shift defined in the dialog requires a separate ⁇ contextshift> element nested within the overall ⁇ contextshifts> tags. The named state of a context shift corresponds to an RTN state.
- Subdialogs may be defined with individual ⁇ dialogfile> elements nested within an overall ⁇ subdialogs> element. Subdialogs can be invoked by the states of an RTN FC. Actions are defined with individual ⁇ actiondef> elements nested within an overall ⁇ actiondefs> element. Actions can be invoked by the transitions of an RTN FC.
- the RTN FC also has some unique properties, such as the start state and default state attributes, which can be very useful.
- start state the name of the state that the RTN FC starts in
- default state the name of the state that the RTN FC defaults to if no other state can be reached.
- local context variables There are, by way of example, three types of values that can be stored in the local context of an RTN or Clarification FC implementation: local context variables, a local context array and a dictionary array. Other values may be stored as well.
- a local context variable is a key/value pair that matches a variable name string to a value string.
- Other variables that may be available include offer typed variables and numeric operations. For example:
- the normal ⁇ array> contains numerically indexed ⁇ var> elements. These elements do not have to have a name attribute.
- the ⁇ dictionary> element can contain ⁇ var> elements referenced by their names. Both types can also contain other arrays. For example:
- Flow controllers also share a global context area across subdialogs and different flow controllers. Variables declared in the global context are accessible by all the FC and any subdialog. Typically, condition elements are used to check the state of the local context and return “true” or “false,” while instructions are used to manipulate values and members of the local context. Instructions can also modify the actions of an FC. Within an FC, it is common to see strings that reference values in the local context. For example, $returnValue references the value of the variable named returnValue. This convention is frequently used in conditions and instructions.
- Conditions may be specified with the ⁇ cond> or ⁇ ucond> elements.
- the ⁇ cond> element takes two arguments, the ⁇ ucond> element only accepts one.
- the following condition types are available in an RTN or clarification FC implementation: Equal conditions, Greater-than conditions, Less-than conditions and XPath conditions.
- Equal (eq) returns true if the first argument is equal to the second. If they are both numeric, a numeric comparison will be made. Either argument may use the $ syntax to refer to local context variables. For example:
- the XPath condition may also be used. This condition uses XPath syntax to check a value in the local context. This is especially useful when a value is described as an XML document, such as the results from the NLU. It is true if the element searched for exists.
- An example of the XPath condition is:
- a context shift is a challenging type of transition to encode throughout an entire application, and it may prevent reuse of existing subdialogs that do not include it.
- the context shift mechanism defines the transition for the entire dialog, and passes it on to subdialogs as well. This means that even if the developer is using a standardized subdialog for, for instance, gathering input, this transition will still be active in the unmodified subdialog.
- a context shift is based on two pieces of information: the input which triggers the shift, and the name of the state where the shift goes (for example, to a different FC, where the concept of state is not specified i.e., rule-based, the system will specify the destination as a subdialog name instead of a specific state).
- a subdialog When a subdialog is created, it inherits the context shifts of its parent dialog. If a shift is fired, the subdialog returns a message that a shift has occurred and the parent dialog is set to the state described by the shift. The only time that a subdialog does not inherit a context shift is when it already has a shift defined for the same trigger concept.
- Table 2 shows the context shifts defined for dialog A:
- Table 3 shows the context shift defined for dialog B:
- the RTN FC allows states to ignore context shifts if specified conditions are met.
- the author wanted to prevent looping in the “Get car type” state. This state could be made exempt from the context shift in order to allow a different action to occur if the concept “Car” was repeated. Note that creating an exemption like this is a good authoring technique for avoiding infinite loops.
- An example output of the application development process is a set of XML (*.fxml) application files, including an application configuration file and one or more dialog files (one top level dialog and any number of sub level dialogs). All application files are preferably compliant with various types of XML schema.
- FIG. 2 illustrates a dialog manager with several flow controllers.
- This figure represents a DM 202 with a loaded flow controller 208 for a top level dialog from an XML data file 204 .
- Another flow controller 210 is loaded from an XML application data file 206 .
- Each dialog and subdialog typically has an associated XML data file.
- the use of multiple flow controllers provides in the present invention an encapsulated, reusable and customizable approach to a spoken dialog.
- the reusable modules do not have any application dependencies and therefore are more capable of being used in a mixed-initiative conversation. This provides an interface definition for a fully encapsulated dialog logic module and its interaction with other FCs.
- Modular or reusable subdialogs have the characteristics that they are initialized by a parent dialog before activation, input is sent to a subdialog until it is complete, results can be retrieved by the parent dialog and context shifts can return flow control to the parent dialog.
- Examples of reusable subdialogs that may be employed to either provide just information to the user or engage in a dialog to obtain information may include a telephone number, a social security number, an account number, an e-mail address, a home or business address, or other topics.
- the development system and method of the invention supports component-based development of complex dialog systems. This includes support for the creation and re-use of parameterized dialog components and the ability to retrieve values from these components using either local results or global variables.
- An example of the reusable components includes a subdialog that requests credit-card information.
- This mechanism for re-usable dialog components pervades the entire system, providing a novel level of support for dialog authors. The author can expect components to operate successfully with respect to the global parameters of the application. Examples of such global parameters comprise the output template and context shift parameters.
- the components can be used recursively within the system, to support recursive dialog flows if necessary.
- the subdialog is isolated from the application dependencies (such as a specific piece of information that the application provides like the top selling books on amazon.com). Being isolated from the application dependencies allows for the subdialog to indicate a context shift and transfer control back to another module without trying to continue down a pre-determined dialog.
- FIGS. 3 and 4 illustrate the use of subdialogs and context shifts.
- FIG. 3 illustrates a mixture of types of dialog modules.
- the control of the dialog at any given time lies within the respective dialog module, which is a logical description of a part of a dialog.
- the dialog module is referred to as a subdialog module when it is handed control by another dialog module.
- the dialog application 302 relates to the spoken dialog service such as the AT&T VoiceTone customer care application.
- the top level FC 304 is loaded as well as several other subdialog FCs such as subdialog-1 306 and subdialog-2 308 . Encapsulation allows each FC 306 and 308 to be loaded separately into the application and the same protocol may always be used for invocation of a subdialog.
- context shifts can go between different types of FCs or between models of subdialog modules.
- a component-based dialog system as developed by the approach disclosed herein allows different decision models of dialogs, such as recursive transition networks (RTN) and rule based systems, to interact seamlessly within an application.
- RTN recursive transition networks
- Rule based systems The algorithms for these dialog models are integrated into the system itself. This means that the author who wants to use an RTN does not have to explain how RTNs work, nor how they interact with other dialog properties. Similarly, if the author wants to create a rule-based dialog, they do not have to create their own rule-based algorithm; instead they can focus on the content.
- subdialogs are fully encapsulated with regard to the model they are based on, so once a subdialog is created using one of the built-in logical models, the subdialog can freely interact with other subdialogs of any model.
- a subdialog which is a rule-based dialog for collecting user information can be called by a top level dialog which is a simple RTN used to route a call.
- FIG. 3 also assists in understanding the concept of the stack.
- a dialog system generated according to this invention operates by using a stack.
- the top dialog module in the stack is indicated in the parameters of the application.
- the control of the dialog always lies with the subdialog at the top of the stack, i.e. the most recently added dialog which has not yet been popped.
- Information can be passed between dialog modules when the modules are pushed or popped.
- the state of the dialog at any moment is described in the language of the decision algorithm used by that dialog module.
- FIG. 4 illustrates a flow controller 402 having several states 404 , 406 .
- a context shift is illustrated as returning control to a specific state 408 within the FC 402 .
- a number of common patterns in dialog development are incorporated into this process to simplify the task of DM creation. These strategies, such as context shifts, chronological shifts, digressions, confirmation, clarification, augmentation, cancel, correction, multi-input, relaxation, repeat, re-prompt and undo have been incorporated into the framework itself. Other strategies following the same pattern of usage may also be incorporated. This allows a particular strategy during a spoken dialog to be easily included if desired, or ignored otherwise.
- a context shift allows the author to describe sudden shifts in conversation.
- Context shifts can be defined in any dialog module, and passed down to all subsequent subdialogs.
- the definition of the context shift describes the state in the defining dialog module that will be returned to in the event that the conditions of the shift are met.
- the conditions of the shift are described in terms of the common memory structure used by all dialog modules, and may include references to the global memory of the system.
- Chronological shift reflect the common user requests to repeat information, or to correct previous input.
- the type of input which constitutes each of these shifts can be defined in any dialog module, and it will be passed along to subdialogs.
- Digressions are also similar to context shifts in the way that they are defined and passed to subdialogs. The difference is that rather than returning control to the dialog module where they are defined, they initiate a new subdialog which is takes control of the conversation. Once the digression subdialog is completed, control returns to the module that had control before the digression.
- a confirmation module confirms an answer and often occurs often within a voice application, and may be required for other dialog strategies.
- the system might require confirmation from the user before the shift is executed.
- the author of the dialog application can create a single dialog module, or use and existing dialog module for all of these tasks.
- the module that will be used is indicated at the application level, and will be used by all occasions of confirmation throughout the application.
- Confirmation occurs when certain data supplied by the user requires explicit confirmation (no matter what confidence level the NLU has returned). This might be done by requesting that the user choose between two tasks, for example.
- Correction occurs when the user corrects or changes information (thus requiring the system to loop back to a previous state or pursue another kind of decision path).
- Multi-input occurs when the user volunteers more input than they have been prompted to supply (and the system captures this info so that later the user only needs to verify information already provided).
- Reprompting occurs when the DM application presents a caller with a repeat prompt using slightly different wording.
- Context Shift dialog pattern allows the application to react to abrupt changes in the flow of conversation with a user.
- a context shift is one of the more tedious types of transitions to encode throughout an entire application, and it typically prevents reuse of existing subdialogs that do not include it.
- the context shift mechanism defines the transition for the entire dialog, and passes it on to subdialogs as well. This means that even if the developer is using a standardized subdialog for, for instance, gathering input, this transition will still be active in the unmodified subdialog.
- a context shift is based on two pieces of information: the input which triggers the shift, and the name of the state where the shift goes.
- a subdialog When a subdialog is created, it inherits the context shifts of its parent dialog. If a shift is fired, the subdialog returns a message that a shift has occurred and the parent dialog is set to the state described by the shift. The only time that a subdialog does not inherit a context shift is when it already has a shift defined for the same trigger concept.
- FIG. 6 illustrates exemplary steps that are performed in the method embodiment of the invention.
- the developer may implement the dialog strategy by selecting the top level flow controller type ( 602 ) as determined by the type of application.
- the RTN FC is generally the appropriate type of top level dialog for most applications. Because RTNs are general state machines, they are usually the right FC for a call flow application.
- the developer breaks the application down into parts that require different FCs below that top level ( 604 ). Based on types of subdialogs the developer intends to write, for example, one may want to incorporate tree logic and/or a rules-based module nested within the states transition module.
- the developer checks for available subdialogs and selects reusable subdialogs for each application part ( 606 ). For example, the reusable InputSD and other subdialogs will be in a developer's library. Thus there are a variety of application parts below the top level flow controller that may be determined Where a subdialog is not available, the method comprises developing a subdialog for each application part that does not have an available subdialog ( 608 ). Once available subdialogs and developed subdialogs are selected, the developer will test and deploy the spoken dialog service using the selected top-level flow controller, selected subdialogs and developed subdialogs ( 610 ).
- FIG. 2 represents a dialog manager 202 with a loaded flow controller 208 for a top level dialog from an XML data file 204 .
- Another flow controller 210 is loaded from an XML application data file 206 .
- the use of multiple flow controllers provides in the present invention an encapsulated, reusable and customizable approach to a spoken dialog. This provides an interface definition for a fully encapsulated dialog logic module and its interaction with other FCs.
- DMML DM application framework with modular logic
- the local context is applied within each FC 208 , 210 to maintain the state of the FC and is independent of the dialog algorithm implemented therein. It is also used to communicate values between FCs.
- An example of a context shift is when a user decides to pursue a new or different goal before the existing goal is completed or the user wants to start the process over. For example, if the user is communicating with a spoken dialog service associated with a bank, the user may be in a dialog to obtain a checking account balance. Part way through the dialog, the user may suddenly request to transfer money from one account to another account. Thus, a context shift occurs that may require the implementation of a subdialog to handle the money transfer context.
- the availability of modular subdialogs for selection by the developer to implement the spoken dialog with the user provides many advantages in terms of time to deployment and cost of development of the spoken dialog system.
- dialog patterns may also be implemented using the modular approach disclosed herein.
- a correction pattern can be implemented to handle the situation where the user corrects or changes information previously given.
- a multi-input pattern can be handled where the user volunteers more information then he or she has been asked to give. Further, in some cases, explicit confirmation of input is required no matter the NLU confidence.
- the multiple flow controllers can provide interchange between each flow controller using a recursive transition network (RTN) which involves storing and manipulating states, transitions and actions between various FCs.
- RTN recursive transition network
- the modular flow controllers are implemented in a rule-based manner where actions are based on certain criteria, a silent count and rejection count are maintained, and slot values are filled or unfilled.
- the subdialogs that are initiated may be initialized by a parent dialog before activation. An input is sent to a subdialog until its use is complete. Results can be retrieved by a parent dialog and context shifts can also return flow control to a parent dialog.
- the process of encapsulation involves loading each FC into the dialog manager application separately. In this regard, the same protocol is used for invocation and for communicating and switching flow control among FCs.
- the context shifts allow the control to pass between different types of FCs.
- FIG. 7 illustrates a method aspect of the invention associated with managing context shifts between FCs. These transitions are defined in a manner that permits each FC to describe a destination for the jump in a customized manner, and to pass the definition of this jump to FCs of other types. This feature allows the content author to seamlessly use diverse systems of dialog logic in combination.
- the DMML maintains a stack of FCs, for example a first FC and a second FC. While the spoken dialog is being managed by a current FC, the system will receive input associated with the user speech and provide responses according to the particular context of the FC. In this dialog, the user may want to switch contexts of the conversation (e.g., from account balance information to a transaction between accounts).
- the spoken dialog system will then receive input associated with the user speech that includes information indicating that a context switch is desired by the user ( 702 ).
- the second FC is added to the stack and will be the recipient of all new inputs from the spoken dialog until it has relinquished control to the parent or first FC.
- Context shifts are inherited by the second FC, and values may be copied from the local context of the first FC.
- new input is received, it is passed to the most recent FC, where it is first compared to at least one context shift ( 704 ).
- the context shifts may be stored within a table. If any of the context shifts are activated, control is passed to the new FC indicated by the context shift, and the FC is set to the state that the shift describes ( 706 ). If no context shift is activated, control passes to the logic of the first FC ( 708 ).
- the current FC can return control to a previous FC whenever its logic dictates.
- RTN actions can be completed with the real actions defined as prompts and grammar activation in the call flow. While the developer is working in the keyboard mode (using the Florence Command Line tool) during development, he or she will just input the expected text for the prompt. Later, when the system is ready to be deployed on the NLS platform the developer will need VoiceXML snippets with the actual prompt definitions (either pre-recorded prompts pointers or text-to-speech commands).
- the developer determines what customization the application requires (i.e., additional java for customized algorithms) and creates application files (an application configuration data file, a top level dialog data file and any necessary subdialog data files) based on a dialog strategy. If necessary, the developer creates an output processing template (or adapt one of the sample templates provided in the Florence or other developer's Toolkit) to format the output for the application.
- Most DM applications include a template file that functions as the output processor, formatting application output as XHTML, XML or VoiceXML code.
- FIG. 5A illustrates a reusable subdialog.
- the reusable subdialog 500 is an input flow controller.
- the states include an S 1 state for receiving input from the user.
- S 0 is an input prompt state. This particular group of states illustrates how to handle silence in the input FC 500 . If silence is heard, the transition C 1 takes the flow to state S 2 which increments the silence count and returns the flow to the get input state S 1 with a silent count parameter.
- FIG. 5B illustrates a more complex RTN reusable subdialog 502 .
- the input prompt S 0 transitions to state S 1 which receives the user input.
- This subdialog handles silence, rejection, a wrong category and a confirmation interaction with the user. If silence is heard, the C 4 transition goes to state S 5 which increments the SilentCount parameter. If a wrong category is received, a wrong category transition C 6 transitions to state S 7 which increments a WrongCategoryCount parameter and returns to state S 1 .
- a rejection input results in a C 5 rejection action transition to state S 6 which increments a RejectionCount parameter.
- the following transitions may bring the flow to the fail state: C 7 for a SilenceFailAction; C 8 for a RejectionFailAction; and C 9 for a WrongCategoryAction transition.
- state S 1 that requires confirmation
- state S 2 that performs a confirmation interaction with the user, represented by states S 3 and S 4 and transitions C 1 , C 2 , and C 3 , which transition to either the fail state or the done state.
- the spoken dialog system can confirm user input.
- top-level dialog of an application must be identified in a ⁇ dialogfile> element in an application configuration data file. All other dialogs in an application are considered subdialogs that can be called from that top-level dialog—or from other subdialogs in the application. Any subdialogs that will be called must be declared in ⁇ dialogfile> tags within the ⁇ subdialogs> element in the code of the calling dialog file.
- a Florence application's configuration file provides key information, such as what the top-level dialog of the application is, what output processor is used, what NLU engine is used, what types of debugging information and log messages will be captured, and so forth.
- the structure and content of an application configuration data file based on the config.fxml template is generally as follows:
- the fxml element tag which is the parent for all other FXML tags used, establishes this as a Florence application file using the FXML schema.
- the configuration tag establishes the file as an application configuration data file type and contains child elements used to define specific configuration data.
- the dialogfile tag identifies the top-level dialog of this application.
- the NLU tag specifies the location of input data by providing host and port number for the NLU (ie, the NLU engine which is to supply the compiled and interpreted data generated from the application user's natural language input).
- the output tag identifies the type of output expected from this DM application and the template, if any, that will format the output.
- VXML VXML template used to format the DM output as VXML. That VXML would be processed by the Florence SLG before and then sent to the Natural Voices TTS engine or prompt player, which would generate a spoken response for the application user.
- the process of building a global context file is discussed next.
- Florence will look for it in the global context file specified by the application's configuration file.
- Global context is built using ⁇ dictionary> and ⁇ var> elements in the same manner as local context built within a dialog file, however global variable definitions are grouped in a separate FXML file.
- Global context functions in the same way as local context, with one exception: the NLU results will only be stored locally.
- the structure and content of a global context file based on the global.fxml template is generally as follows:
- a global context file used by an application might look more like the following:
- the fxml element tag establishes this as a Florence application file using the FXML schema and serves as a container for all other FXML tags used in this file.
- the global tag establishes the file as a global context file type and contains child elements used to define specific variables and parameters.
- the var tag is used here to specify global context variables.
- the array tag is used here to define a global context array.
- the dictionary tag is used here for a look-up list of global variable names.
- RTN FC Dialog File A Florence application's top-level dialog is most often a dialog based on the Recursive Transition Network (RTN) flow controller (FC) implementation.
- RTN dialogs are based on the concepts of states and transitions between states.
- the fxml element tag establishes this as a Florence application file using the FXML schema and serves as a container for all other FXML tags used in this file.
- the rtn tag establishes this as a dialog based on the RTN FC and contains all the child elements used to build the RTN dialog, including tags to: local to describe local context, subdialogs to identify subdialogs, actiondefs to define actions, states to specify states (with associated instructions), transitions to specify transitions (with associated actions), contextshift to identify context shifts, and chronoshift to identify chronoshifts.
- the Florence DM engine's built-in output processor uses an application's dialog components in conjunction with its output template to prepare appropriate output in response to user input.
- this output is what will ultimately generate the response to be returned to the customer.
- This output can take the form of simple text, but most typically the output is formatted by the application's output processor—a VoiceXML template—as VoiceXML code containing speech text prompts. Those speech text prompts are then used by the Natural Voices TTS engine to generate the system's spoken response to the customer.
- the Output Processor formats Florence output into text, VoiceXML, or whatever other type of string output it has been specialized to provide.
- the content comes from an Action object in the currently active dialog. For the Output Processor to work correctly, it must be able to get the content it needs from the Action object. This creates a strong coupling between these two components; they will usually be created in pairs.
- the ⁇ output> element defined in an application's configuration data file must specify a VXML template (such as the VoiceXMLTemplate.vxml file that is supplied with the Florence examples).
- the VXML template not only uses the text of an action, which is part of a normal action definition, but it can also use arbitrary blocks of VXML code which have been associated with the action.
- the method of developing a dialog manager preferably includes a step of selecting an available reusable subdialog for each application part.
- the example reusable dialog is the input subdialog (referred to as the InputSD).
- the input subdialog is a reusable dialog for collecting input from the user. It is capable of handling silences, rejections, low confidence NLU results, and explicit confirmation and it can be configured with custom prompts and patience levels for each invocation.
- This section describes how to configure the InputSD, what behavior to expect from it, and how to retrieve results from it. It also includes an example of how to use the InputSD.
- the InputSD uses the actions copied to it when it is invoked to handle specific problems that arise during the input process.
- the InputSD checks to see if its patience for that sort of problem has been exceeded. If it has, then the dialog fails and ends. If its patience has not been exceeded, the InputSD plays a prompt from the list of prompts that have been sent to the subdialog to apply to special circumstances.
- the special circumstances are silence, rejection, and low-confidence NLU value.
- NLU value returned with a low confidence score the user is given the opportunity to confirm the value with a yes or no answer (unless the dialog is already trying to get a yes/no value). It is also possible to request that the dialog always confirm a value before it is returned.
- the InputSD handles this in a manner similar to the handling of low-confidence values.
- Input values are the local variables that can be configured when the InputSD is invoked. These variables are set using ⁇ set> in an ⁇ entersubdialog> element. Any prompts that will be used in the InputSD must also be copied in this instruction set with a ⁇ copy> element. See the sample code at the end of this section for an example.
- Allowed input values include: InputPrompt—this is the name of the prompt to play when the InputSD begins; YN—set this to “true” if the dialog is being invoked to collect a yes or no response (it defaults to “false”); YvalueName—this is the value that the dialog will recognize as “yes” (it defaults to “discourse_yes”); NvalueName—this is the value that the dialog will recognize as “no” (it defaults to “discourse_no”); SilenceCategory—this is the value that the dialog will recognize as a silence (it has no default); RejectCategory—this is the value that the dialog will recognize as a rejection (it has no default); ConfidenceThreshold—the input must have a confidence level above this threshold (it defaults to 0); and ExplicitConfirm—if this dialog must always confirm responses, set this to “true” (it defaults to “false”).
- Each of the following variables describes how many times the dialog will tolerate a particular type of input failure before failing. Each defaults to 0: SilencePatience; RejectionPatience; ConfidencePatience—this applies to low-confidence, unconfirmed inputs; and confirmPatience—this is the number of times an explicit confirmation can receive a “no” answer.
- the following variables are action names.
- Local context array variables the ⁇ array> elements within the ⁇ local> element of an RTN FC dialog file
- the InputSD iterates over each of these sets of actions for a particular type of input situation.
- RetumConcept the NLU concept that was the InputSD received
- RetumValue the text received by the InputSD
- RetumConfidence the confidence score of the result
- result the actual NLU result
- Success true or false.
- Embodiments within the scope of the present invention may also include computer-readable media for carrying or having computer-executable instructions or data structures stored thereon.
- Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer.
- Such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer-executable instructions or data structures.
- a network or another communications connection either hardwired, wireless, or combination thereof
- any such connection is properly termed a computer-readable medium. Combinations of the above should also be included within the scope of the computer-readable media.
- Computer-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions.
- Computer-executable instructions also include program modules that are executed by computers in stand-alone or network environments.
- program modules include routines, programs, objects, components, and data structures, etc. that perform particular tasks or implement particular abstract data types.
- Computer-executable instructions, associated data structures, and program modules represent examples of the program code means for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps.
- Embodiments of the invention may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Computational Linguistics (AREA)
- Multimedia (AREA)
- Human Computer Interaction (AREA)
- Acoustics & Sound (AREA)
- Theoretical Computer Science (AREA)
- Artificial Intelligence (AREA)
- Quality & Reliability (AREA)
- Signal Processing (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- User Interface Of Digital Computer (AREA)
- Machine Translation (AREA)
Abstract
Description
- The present application is a continuation of U.S. patent application Ser. No. 13/926,366, filed Jun. 25, 2013, which is a continuation of U.S. patent application Ser. No. 12/201,423, filed on Aug. 29, 2008, now U.S. Pat. No. 8,473,299, issued Jun. 25, 2013, which is a continuation of U.S. patent application Ser. No. 10/790,495, filed on Mar. 1, 2004, now U.S. Pat. No. 7,421,393, issued Sep. 2, 2008, which is a non-provisional application of U.S. Provisional Patent Application No. 60/470,824, filed May 15, 2003, the contents of which are incorporated herein by reference in their entirety.
- This application is related to the following applications: U.S. patent application Ser. No. 10/763,085, filed Jan. 22, 2004, now abandoned, Attorney Docket No. 2002-0354 entitled “System and Method to Disambiguate and Clarify User Intention in a Spoken Dialog System”; U.S. patent application Ser. No. 10/790,159, filed Mar. 1, 2004, now U.S. Pat. No. 7,412,393, Attorney Docket No. 2002-0355 entitled “Method for Developing a Dialog Manager Using Modular Spoken-Dialog Components”; and U.S. patent application Ser. No. 10/790,517, filed Mar. 1, 2004, now U.S. Pat. No. 7,430,510, Attorney Docket No. 2002-0355B entitled “System and Method of Using Modular Spoken-Dialog Components to Handle Context Shifts in Spoken Dialog Systems”. The contents of these applications are incorporated herein by reference in their entirety.
- 1. Field of the Invention
- The present invention relates to spoken dialog systems and more specifically to spoken dialog system and a dialog manager generated using a reusable dialog modular development approach.
- 2. Introduction
- The present invention relates to spoken dialog systems and to the dialog manager module within such a system. The dialog manager controls the interactive strategy and flow once the semantic meaning of the user query is extracted. There are a variety of techniques for handling dialog management. Several examples may be found in Huang, Acero and Hon, Spoken Language Processing, A Guide to Theory, Algorithm and System Development, Prentice Hall PTR (2001), pages 886-918. Recent advances in large vocabulary speech recognition and natural language understanding have made the dialog manager component complex and difficult to maintain. Often, existing specifications and industry standards such as Voice XML and SALT (Speech Application Language Tags) have difficulty with more complex speech applications.
- Development of a dialog manager continues to require highly-skilled and trained developers. The process of designing, developing, testing and deploying a spoken dialog service having an acceptably accurate dialog manager is costly and time-consuming. As the technology continues to develop, consumers further expect spoken dialog systems to handle more complex dialogs. As can be appreciated, higher costs and technical skills are required to develop more complex spoken dialog systems.
- Given the improved ability of large vocabulary speech recognition systems and natural language understanding capabilities, what is needed in the art is a system and method that provides an improved development process for the dialog manager in a complex dialog system. Such improved method should simplify the development process, decrease the cost to deploy a spoken dialog service, and utilize reusable components. In so doing, the improvement method should also enable the author of a dialog system to focus efforts on the key areas of content that define an individual application.
- Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The features and advantages of the invention may be realized and obtained by means of the instruments and combinations particularly pointed out in the appended claims. These and other features of the present invention will become more fully apparent from the following description and appended claims, or may be learned by the practice of the invention as set forth herein.
- An embodiment of the invention relates to a dialog manager for use within a spoken dialog service, the dialog manager generated according to a method comprising selecting a top level flow controller, selecting available reusable subdialogs for each application part below the top level flow controller, developing a subdialog for each application part not having an available subdialog and testing and deploying the spoken dialog service using the selected top level flow controller, selected reusable subdialogs and developed subdialogs. The top level flow controller, reusable subdialogs and developed subdialogs interact with each other independent of their decision model. In other words, dialog modules designed using rule-based decision models, recursive transition network (RTN) decision models or other decision models can all seamlessly communicate with each other without the need of the developer to design specific rules governing their interaction. In this regard, functions that are dependent on or specific to a particular application, such as presenting the top book sales associated a bookseller website, are not associated with the reusable subdialogs. Further, when a user causes a context shift while a reusable subdialog is controlling the conversation, the system returns a context shift indication and a destination state and returns control of the dialog to a top level controller or parent dialog. This enables the subdialogs to be reusable in different applications. Other embodiments of the invention include but are not limited to (1) a modular subdialog having certain characteristics such that it can be selected and incorporated into a dialog manager below a top level flow controller. The modular subdialog can be called up by the top level flow controller to handle specific tasks and receive context data and return data to the top level flow control gathered from its interaction with the user as programmed; (2) a dialog manager generated according to the method set forth herein; (3) a computer readable medium storing program instructions or spoken dialog system components; and (4) a spoken dialog service having a dialog manager generated according to the process set forth herein.
- In order to describe the manner in which the above-recited and other advantages and features of the invention can be obtained, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope, the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which:
-
FIG. 1 illustrates the basic spoken dialog service; -
FIG. 2 illustrates a flow controller in the context of a dialog manager; -
FIG. 3 illustrates a dialog application top level flow controller and example subdialogs; -
FIG. 4 illustrates a context shift associated with a flow controller; -
FIG. 5A illustrates a reusable subdialog; -
FIG. 5B illustrates an RTN reusable subdialog; -
FIG. 6 illustrates a method aspect of the present invention; and -
FIG. 7 illustrates another method aspect of the invention associated with context shifts. - The various embodiments of the invention will be explained generally in the context of AT&T speech products and development tools. However, the present invention is not limited to any specific product or application development environment.
-
FIG. 1 provides the basic modules that are used in a spokendialog system 100. Auser 102 that is interacting with the system will speak a question or statement. An automatic speech recognition (ASR)module 104 will receive and process the sound from the speech. The speech is recognized and converted into text. AT&T's Watson ASR component is an example of such an ASR module. The text is transmitted to a spoken language understanding (SLU) module 106 (or natural language understanding (NLU) module) that determines the meaning of the speech, or determines the user's intent in the speech. This involves interpretation as well as decision: interpreting what task the caller wants performed and determining whether there is clearly a single, unambiguous task the caller is requesting—or, if not, determining actions that can be taken to resolve the ambiguity. TheNLU 106 uses its language models to interpret what the caller said. The NLU processes the spoken language input wherein the concepts and other extracted data are transmitted (preferably in XML code) from theNLU 106 to theDM application 108 along with a confidence score. The (DM)module 108 processes the received candidate intents or purposes of the user's speech and generates an appropriate response. In this regard, theDM 108 manages interaction with the caller, deciding how the system will respond to the caller. This is preferably a joint process of theDM engine 108 running on a Natural Language Services (NLS) platform (such as AT&T's infrastructure for NL services, for example) and thespecific DM application 108 that it has loaded and launched. TheDM engine 108 manages dialog with the caller by applying the compiled concepts returned from theNLU 106 to the logic models provided by theDM application 108. This determines how the system interacts with a caller, within the context of an ongoing dialog. The substance of the response is transmitted to a spoken language generation component (SLG) 110 which generates words to be spoken to thecaller 102. The words are transmitted to a text-to-speech module 112 that synthesizes audible speech that theuser 102 receives and hears. TheSLG 110 either plays back pre-recorded prompts or real-time synthesized text-to-speech (TTS). AT&T's Natural Voices® TTS engine provides an example of a TTS engine that is preferably used. Various types of data andrules 114 are employed in the training and run-time operation of each of these components. - An
example DM 108 component is the AT&T Florence DM engine and DM application development environment. The present invention relates to the DM component and will provide a novel approach to development and implementation of theDM module 108. Other embodiments of the invention include a spoken dialog system having a DM that functions according to the disclosure here, a DM module independent of a spoken dialog service or other hardware or firmware, a computer-readable medium for controlling a computing device and various methods of practicing the invention. These various embodiments will be understood from the disclosure here. - A spoken dialog system or dialog manager (as part of a spoken dialog system) will operate on a computing device such as the well-known computer system having a computer processor, volatile memory, a hard disc, a bus that transmits information from memory through the processor and to and from other computer components. Inasmuch as the basic computing architecture and programming languages evolve, the present invention is not limited to any specific computing structure but may be operable on any state-of-the-art device or network configuration.
- AT&T's Florence dialog management environment provides a complete framework for building and testing advanced natural language automated dialog applications. The core of Florence is its object-oriented framework of Java classes and standard dialog patterns. This serves as an immediate foundation for rapid development of dialog infrastructure with little or no additional programming.
- Along with a dialog infrastructure, Florence offers tools to create a local development and test environment with many convenient and time-saving features to support dialog authoring. Florence also supplies a key runtime component for the VoiceTone Dialog Automation platform—the Florence Dialog Manager (DM) engine, an Enterprise Java Bean (EJB) on the VoiceTone/NLS J2EE application server. Once a DM application is deployed on a platform such as the VoiceTone platform, the DM engine uses the logic built into the application's dialogs to manage interactions with end-users within the context of an on-going dialog.
- Whatever a dialog flow control logic model is active, the
DM application 108 will determine, for example, whether it is necessary to prompt the caller to get confirmation or clarification and whether the caller has provided sufficient information to establish an unambiguous course of action. When the task to be performed is unambiguous, the DM engine's output processor uses the DM application's dialog components and output template to prepare appropriate output. Output is most often formatted as VoiceXML code containing speech text prompts that will be used to generate a spoken response to the caller. - Note that although VoiceXML is the most typical output, a
DM application 108 can also be configured to provide output in any XML-based language only replacing the appropriate output template. TheDM application 108 may also generate output configured in other ways. When plain text output is sufficient (as might be the case during application development/debugging), Florence's own simple output processor can be used in lieu of any output template. The DM's spoken language generator (SLG) 110 helps generate the system's response to thecaller 102. Output (such as VoiceXML code with speech text, for example) generated by the Florence output processor using a specific output template is run through theSLG 110 before it is sent to a text-to-speech (TTS)engine 112. In real production grade services, both the DM and 108 theNLU 106 engines are preferably Enterprise Java Beans (EJBs) running on the NLS J2EE application server. The ASR and TTS engines communicate with the NLS server via a telephony server or some other communication means. Using EJBs is one way to implement the business logic and servlets or JSP pages are also alternative standard-based options. - A DM application supplies dialog data and logical models pertaining to the kinds of tasks a user might be trying to perform and the dialog manager engine implements the call flow logic contained in the DM application to assist in completing those tasks. As tasks are performed, the dialog manager is also updating the dialog history (the record of the system's previous dialog interaction with a caller) by logging information representing an ongoing history of the dialog, including input received, decisions made, and output generated.
- Florence DM applications can be created and debugged in a local desktop development environment before they are deployed on the NLS J2EE application server. The Florence Toolkit includes a local copy of the XML schema, a local command line tool, and a local NLU server specifically for this purpose. Ultimately, however, DM applications that are to be deployed on the NLS server need to be tested with to NLS technology components residing on the J2EE server.
- An important concept defined in the Florence DM is the Flow Controller (FC) logic. A Flow Controller is the abstraction for pluggable dialog strategy modules. The dialog strategy model controls the flow of dialog when a user “converses” with the system. Dialog strategy implementations can be based on different types of dialog flow control logic models. Different algorithms can be implemented and made available to the DM engine without changing the basic interface. For example, customer care call routing systems are better described in terms of RTNs (Recursive Transition Networks). Complex knowledge-based tasks could be synthetically described by a variation of knowledge trees. Clarification FCs are basically decision trees, where dialog control passes from node to node along branches and are discussed in U.S. patent application Ser. No. 10/763,085, filed Jan. 22, 2004, now abandoned, Attorney Docket No. 2002-0354 entitled “System and Method to Disambiguate and Clarify User Intention in a Spoken Dialog System”. Plan-based dialogs are effectively defined by rules and constraints (rule-based). Florence FC provides a synthetic XML-based language to author the appropriate dialog strategy. Dialog strategy algorithms are encapsulated using object oriented paradigms. This allows dialog authors to write sub-dialogs with different algorithms, depending on the nature of the task and use them interchangeably exchanging variables through the local and global contexts. The disclosure below relates to RTN FCs.
- RTN FCs are finite state models, where a dialog control passes from one state to another and transitions between states have specific triggers. This decision system uses the notion of states connected by arcs. The path through the network is decided based on the conditions associated with the arcs. Each state is capable of calling a new subdialog. Additional types of FC implementations include a rules-based model. In this model, the author writes rules which are used to make decisions about how to interact with the user. The RTN FC is the preferred model for automated customer care services. All the FC family of dialog strategy algorithms, such as the RTN FC, the clarification FC, and the rule-based FC implementations support common dialog flow control features, such as context shifts, local context, actions, and subdialogs.
- In general, the RTN FC is a state machine that uses states and transitions between states to control the dialog between a user and a DM application. Where some variables are defined at the state level (using slots, for example, as a local context), these are often referred to as Augmented Transition Networks. See, e.g., D. Bobrow and B. Fraser, “An Augmented State Transition Network Analysis Procedure”, Proceedings of the IJCAI, pages 557-567, Washington D.C., May 1969. For simplicity, the present document refers to RTNs only. If an application is using an RTN FC implementation in its currently active dialog, when the DM application receives user input, the DM engine applies the call logic defined in that RTN FC implementation to respond to the user in an appropriate manner. The RTN FC logic determines which state to advance to based on the input received from the caller. There may be associated sets of instructions that will be executed upon entering this state. (A state can have up to four or more instruction sets.) The transition from one state to another may also have an associated set of conditions that must be met in order to move to the next state or associated actions that are invoked when the transition occurs.
- Next is described a possible implementation of RTNs using an XML-based language. Each RTN state is defined in the XML code of a dialog data file with a separate <state> element nested within the overall <states> element. The attributes of an RTN <state> element include name, subdialog and pause. The name attribute is the identifier of the state; it can be any string. The subdialog attribute is the name of the FC invoked as a subdialog. If this attribute is left out, the state will not create a subdialog. The pause attribute determines whether the RTN FC will pause. If this is set to true, the RTN controller will pause before exiting to get new user input. Note that if the state invokes a subdialog, it will not pause before the subdialog is invoked, but will pause after it returns control. For example:
-
<state name=“GET_SELECTION” subdialog=“InputSD” pause=“false”> <!--since pause is false, it will not wait for new input after the subdialog--> <state > - Two aspects of state behavior should be noted. First, all instructions that modify the local context of the FC occur inside of states. Second, only states modify the local context of an RTN FC by executing instructions. Transitions (see below) do not execute instructions, although they can execute actions. The behavior of a state occurs in stages. In a preferred embodiment, there are six stages, as described below. These are only exemplary stages, however, and other stages are contemplated as within the scope of the invention.
- The first stage relates to state entry instructions. The <enterstate> set of instructions is executed immediately when a transition delivers control to the state. If a state is reached by a context shift or a chronoshift, these instructions are not executed. A chronoshift denotes a request to back trace the dialog execution to a previous dialog turn. Chronoshifts typically also involved removing a previous dialog from the stack to give control to the previous dialog. Also, the initial state of an RTN does not execute these instructions; however, if the RTN FC passes control to this state because it is the default state of the RTN FC, it will execute these instructions. The following is an example from a dialog file's XML code where a <set> element nested within an <enterstate> element includes entry instructions:
-
<state name=“SPANISH_STATE”> <enterstate> <set name=“salutation” expr=“Adios!”/> </enterstate> </state> - The second stage relates to subdialog creation. If the state has a subdialog, then it is created at this stage. The name of the subdialog is provided as the value of the subdialog= attribute of the <state> element. The following is an example of the syntax for a <state> element which calls a subdialog named InputSD:
-
- <state name=“GET_SELECTION” subdialog=“InputSD”/>
- The third stage relates to subdialog entry instructions. The <entersubdialog> set of instructions is invoked when the state creates a subdialog. Typically, instructions in this stage affect both the dialog and the subdialog. For example, the <set> instruction will retrieve values from the parent dialog and set values in the subdialog. This is useful for passing arguments to a subdialog before it executes. In one aspect of the invention, the invoked subdialog is pushed to the stop of the stack of dialog modules so that the invoked subdialog can manage the spoken dialog and interact with the user.
- The fourth stage relates to subdialog execution. If a subdialog was created in stage 2 (the subdialog creation stage), it is started in this stage. Input will be directed to the subdialog until it returns control to the dialog.
- The fifth stage relates to subdialog exit instructions. The <exitsubdialog> set of instructions is invoked when the subdialog returns control to the dialog. Typically, instructions in this stage affect both the dialog and the subdialog. This is useful for retrieving values from a subdialog when it is complete. In one aspect of the invention, when the control of the spoken dialog exits from an invoked subdialog module, the subdialog module is popped off the dialog module stack.
- The sixth stage relates to state exit instructions. The <exitstate> set of instructions is executed when a transition is used to exit a state or the RTN shifts control to the default state. These instructions are not executed if the state is left by a context shift or chronoshift, nor are they executed if this is a final state in this RTN. The six stages of a state and associated instruction sets are summarized in the table below. When a state has passed through all six of these stages (including those with no associated instructions) it will advance to a new state.
-
TABLE 1 State Instruction Sets Stage Instruction Set State Entry Use an <enterstate> element with a <set> element nested within it to identify a set of instructions associated with entering this state. Subdialog No instructions are used in Creation this stage, however, the subdialog attribute of the <state> element can be used to identify the subdialog being called. Subdialog Entry Use an <entersubdialog> element with a <set> element nested within it to identify a set of instructions associated with entering this subdialog. Subdialog No instructions are used in this stage. Execution Subdialog Exit Use an <exitsubdialog> element with a <set> element nested within it to identify a set of instructions associated with exiting this subdialog. State Exit Use an <exitstate> element with a <set> element nested within it to identify a set of instructions associated with exiting this state. - Each RTN transition is defined in the XML code of the dialog file with a separate <transition> element nested within the overall <transitions> element. The attributes of a <transition> element include: name=, from=, to=, and else=. For example:
-
<transition name=″GERMAN_SELECTED″ from=″GET_SELECTION″ to=″GERMAN_STATE″ else=”true”> - In this example, the name= attribute is the identifier for the RTN transition. It can be any unique string. The from= attribute is the identifier of the source state, and the to= attribute is the identifier of the destination state. The else= attribute determines whether and when other transitions can be used. If the else= attribute is given a “true” value, then this transition will only be invoked if no other transitions can be used.
- Each <transition> can have a set of conditions defined in a <conditions> element. This element must be evaluated to true in order for the transition to be traversable. Each <transition> can also have an element of type <actions>. This element contains the <action> elements which will be executed if this transition is selected. The following example comes from a sample application where callers order foreign language movies:
-
<transition name=″FRENCH_SELECTED″ from=″GET_SELECTION″ to=″FRENCH_STATE″> <actions> <action>FRENCH_MOVIE</action> </actions> <conditions> <cond oper=”eq” expr1=″$successfulInput″ expr2=″true″ /> <cond oper=”eq” expr1=″$language″ expr2=″french″ /> </conditions> </transition> - Transitions can have conditions and actions associated with them, but not instructions. Transitions do not execute instructions; only states can affect the local context in an RTN FC.
- There are conditions associated with each transition. A transition can have an associated set of conditions which must all be fulfilled in order to be traversed—or, it can be marked as an “else transition”, which means it will be traversed if no other transition is eligible. Transitions with conditions that have been satisfied have priority over else transitions. If a transition has no conditions, it is treated as an else transition. If multiple transitions are eligible, which of the transitions will be selected as undefined—and which else transition will be selected if there is more than one is also undefined. Here is an example of a transition with two conditions:
-
<transition name=″ENGLISH_SELECTED″ from=″GET_SELECTION″ to=″ENGLISH_STATE″> <conditions> <cond oper=”eq” expr1=″$successfulInput″ expr2=″true″/> <cond oper=”eq” expr1=″$language″ expr2=″english″/> </conditions> </transition> - Here is an example of an else condition:
-
<transition name=″ENGLISH_SELECTED″ from=″GET_SELECTION″ to=″ENGLISH_STATE″ else = “true”/> - There are also actions associated with each transition. In addition to moving the RTN to a new state, another effect of traversing a transition is execution of actions associated with that transition. An action is used to communicate with the application user. A transition can invoke any number of actions. This is an example of a transition with an action:
-
<transition name=“INTRO_PROMPT” from=“START_STATE” to=“CORRECT_STATE”> <actions> <action>INTRO_PROMPT</action> </actions> </transition> - The RTN FC is responsible for keeping track of action data. In the example above, INTRO_PROMPT is a label that is used to look up the action data. In addition to states and transitions, other components of the RTN FC include: Local context, Context shifts, Subdialogs and Actions.
- The concept of a local context, implemented in the XML code of the dialog data file with the <context> element, is particularly important. Local context is a memory space for tracking stored values in an application. These values can be read and manipulated using conditions and instructions. Instructions modify the local context from RTN states. Context shifts are implemented with the <contextshifts> element. Each context shift defined in the dialog requires a separate <contextshift> element nested within the overall <contextshifts> tags. The named state of a context shift corresponds to an RTN state.
- Subdialogs may be defined with individual <dialogfile> elements nested within an overall <subdialogs> element. Subdialogs can be invoked by the states of an RTN FC. Actions are defined with individual <actiondef> elements nested within an overall <actiondefs> element. Actions can be invoked by the transitions of an RTN FC. The RTN FC also has some unique properties, such as the start state and default state attributes, which can be very useful. In an application's FXML dialog files, the start= and default= attributes of the <rtn> element allow the developer to specify the start state (the name of the state that the RTN FC starts in) and the default state (the name of the state that the RTN FC defaults to if no other state can be reached). Again, from the movie rental example:
-
- <rtn name=“MovieRentalSD” start=“START_STATE” default=“DEFAULT_STATE”> </rtn>
- There are, by way of example, three types of values that can be stored in the local context of an RTN or Clarification FC implementation: local context variables, a local context array and a dictionary array. Other values may be stored as well. A local context variable is a key/value pair that matches a variable name string to a value string. Other variables that may be available include offer typed variables and numeric operations. For example:
-
- <var name=“successfulInput” expr=“false”/>
- The normal <array> contains numerically indexed <var> elements. These elements do not have to have a name attribute. The <dictionary> element can contain <var> elements referenced by their names. Both types can also contain other arrays. For example:
-
- <array name=“SilenceActions”><var expr=“SILENCE1”/><var expr=“SILENCE2”/></array>
- As mentioned above, local context variables can be referred to in conditions and instructions. Every FC implementation will provide some way to do this. Flow controllers also share a global context area across subdialogs and different flow controllers. Variables declared in the global context are accessible by all the FC and any subdialog. Typically, condition elements are used to check the state of the local context and return “true” or “false,” while instructions are used to manipulate values and members of the local context. Instructions can also modify the actions of an FC. Within an FC, it is common to see strings that reference values in the local context. For example, $returnValue references the value of the variable named returnValue. This convention is frequently used in conditions and instructions.
- Conditions may be specified with the <cond> or <ucond> elements. The <cond> element takes two arguments, the <ucond> element only accepts one. The following condition types are available in an RTN or clarification FC implementation: Equal conditions, Greater-than conditions, Less-than conditions and XPath conditions.
- Equal (eq) returns true if the first argument is equal to the second. If they are both numeric, a numeric comparison will be made. Either argument may use the $ syntax to refer to local context variables. For example:
-
- <cond oper=“eq” expr1=“$inputConcept” expr2=“discourse_yes”/>
- Greater-than (gt) returns true if the first argument is greater than the second. Otherwise it is identical to EQCondition. For example:
-
- <cond oper=“gt” expr1=“$inputConfidence”expr2=“0.8”/>
- Less-thanReturns (lt) returns true if the first argument is less than the second. Otherwise identical to EQCondition. For example:
-
- <cond oper=“lt” expr1=“$inputConfidence”expr2=“0.8”/>
- The XPath condition may also be used. This condition uses XPath syntax to check a value in the local context. This is especially useful when a value is described as an XML document, such as the results from the NLU. It is true if the element searched for exists. An example of the XPath condition is:
-
- <ucond oper=“xpath” expr=“result/interpretation/input/noinput”/>
- A context shift is a challenging type of transition to encode throughout an entire application, and it may prevent reuse of existing subdialogs that do not include it. The context shift mechanism defines the transition for the entire dialog, and passes it on to subdialogs as well. This means that even if the developer is using a standardized subdialog for, for instance, gathering input, this transition will still be active in the unmodified subdialog.
- A context shift is based on two pieces of information: the input which triggers the shift, and the name of the state where the shift goes (for example, to a different FC, where the concept of state is not specified i.e., rule-based, the system will specify the destination as a subdialog name instead of a specific state). When a subdialog is created, it inherits the context shifts of its parent dialog. If a shift is fired, the subdialog returns a message that a shift has occurred and the parent dialog is set to the state described by the shift. The only time that a subdialog does not inherit a context shift is when it already has a shift defined for the same trigger concept.
- For example, Table 2 shows the context shifts defined for dialog A:
-
TABLE 2 Context Shifts Example - Dialog A Definitions Trigger Concept Set Destination State Car “Car rental” Hotel “Hotel reservation” Plane “Flight reservation” - Table 3 shows the context shift defined for dialog B:
-
TABLE 3 Context Shifts Example - Dialog B Definitions Trigger Concept Set Destination State Car “Get car type” - Then, when A calls B, the context shifts of B will be as shown in Table 4:
-
TABLE 4 Context Shifts Example - When Dialog A Calls Dialog B Trigger Concept Set Destination State Car “Get car type” Hotel Dialog A: “Hotel reservation” Plane Dialog A: “Flight reservation” - It is also possible for an FC to override the shift. For example, the RTN FC allows states to ignore context shifts if specified conditions are met. Suppose the author wanted to prevent looping in the “Get car type” state. This state could be made exempt from the context shift in order to allow a different action to occur if the concept “Car” was repeated. Note that creating an exemption like this is a good authoring technique for avoiding infinite loops.
- An example output of the application development process is a set of XML (*.fxml) application files, including an application configuration file and one or more dialog files (one top level dialog and any number of sub level dialogs). All application files are preferably compliant with various types of XML schema.
-
FIG. 2 illustrates a dialog manager with several flow controllers. This figure represents aDM 202 with a loadedflow controller 208 for a top level dialog from anXML data file 204. Anotherflow controller 210 is loaded from an XML application data file 206. Each dialog and subdialog typically has an associated XML data file. The use of multiple flow controllers provides in the present invention an encapsulated, reusable and customizable approach to a spoken dialog. The reusable modules do not have any application dependencies and therefore are more capable of being used in a mixed-initiative conversation. This provides an interface definition for a fully encapsulated dialog logic module and its interaction with other FCs. Modular or reusable subdialogs have the characteristics that they are initialized by a parent dialog before activation, input is sent to a subdialog until it is complete, results can be retrieved by the parent dialog and context shifts can return flow control to the parent dialog. - Examples of reusable subdialogs that may be employed to either provide just information to the user or engage in a dialog to obtain information may include a telephone number, a social security number, an account number, an e-mail address, a home or business address, or other topics.
- The development system and method of the invention supports component-based development of complex dialog systems. This includes support for the creation and re-use of parameterized dialog components and the ability to retrieve values from these components using either local results or global variables. An example of the reusable components includes a subdialog that requests credit-card information. This mechanism for re-usable dialog components pervades the entire system, providing a novel level of support for dialog authors. The author can expect components to operate successfully with respect to the global parameters of the application. Examples of such global parameters comprise the output template and context shift parameters. The components can be used recursively within the system, to support recursive dialog flows if necessary. Therefore, while a subdialog is controlling the conversation, if a context shift occurs, the subdialog is isolated from the application dependencies (such as a specific piece of information that the application provides like the top selling books on amazon.com). Being isolated from the application dependencies allows for the subdialog to indicate a context shift and transfer control back to another module without trying to continue down a pre-determined dialog.
-
FIGS. 3 and 4 illustrate the use of subdialogs and context shifts.FIG. 3 illustrates a mixture of types of dialog modules. The control of the dialog at any given time lies within the respective dialog module, which is a logical description of a part of a dialog. The dialog module is referred to as a subdialog module when it is handed control by another dialog module. As shown inFIG. 3 , thedialog application 302 relates to the spoken dialog service such as the AT&T VoiceTone customer care application. Thetop level FC 304 is loaded as well as several other subdialog FCs such as subdialog-1 306 and subdialog-2 308. Encapsulation allows eachFC - Furthermore, context shifts can go between different types of FCs or between models of subdialog modules. In this regard, a component-based dialog system as developed by the approach disclosed herein allows different decision models of dialogs, such as recursive transition networks (RTN) and rule based systems, to interact seamlessly within an application. The algorithms for these dialog models are integrated into the system itself. This means that the author who wants to use an RTN does not have to explain how RTNs work, nor how they interact with other dialog properties. Similarly, if the author wants to create a rule-based dialog, they do not have to create their own rule-based algorithm; instead they can focus on the content. Individual subdialogs are fully encapsulated with regard to the model they are based on, so once a subdialog is created using one of the built-in logical models, the subdialog can freely interact with other subdialogs of any model. For example, a subdialog which is a rule-based dialog for collecting user information can be called by a top level dialog which is a simple RTN used to route a call.
-
FIG. 3 also assists in understanding the concept of the stack. A dialog system generated according to this invention operates by using a stack. The top dialog module in the stack is indicated in the parameters of the application. When a subdialog is called, it is pushed onto the stack, and when it exits it is popped off of the stack. The control of the dialog always lies with the subdialog at the top of the stack, i.e. the most recently added dialog which has not yet been popped. - Information can be passed between dialog modules when the modules are pushed or popped. There is also a global memory space which can be used by any dialog module. There is a common implementation of local memory which allows information to be passed to and from a subdialog when it is created and completed, respectively. Within each module, the state of the dialog at any moment is described in the language of the decision algorithm used by that dialog module.
-
FIG. 4 illustrates aflow controller 402 havingseveral states specific state 408 within theFC 402. A number of common patterns in dialog development are incorporated into this process to simplify the task of DM creation. These strategies, such as context shifts, chronological shifts, digressions, confirmation, clarification, augmentation, cancel, correction, multi-input, relaxation, repeat, re-prompt and undo have been incorporated into the framework itself. Other strategies following the same pattern of usage may also be incorporated. This allows a particular strategy during a spoken dialog to be easily included if desired, or ignored otherwise. - Several of the dialog module strategies are described next. A context shift allows the author to describe sudden shifts in conversation. Context shifts can be defined in any dialog module, and passed down to all subsequent subdialogs. The definition of the context shift describes the state in the defining dialog module that will be returned to in the event that the conditions of the shift are met. The conditions of the shift are described in terms of the common memory structure used by all dialog modules, and may include references to the global memory of the system. When the context shift is fired, control returns to the dialog module where it was defined, popping all subdialog modules off of the control stack.
- Chronological shift reflect the common user requests to repeat information, or to correct previous input. The type of input which constitutes each of these shifts can be defined in any dialog module, and it will be passed along to subdialogs.
- Digressions are also similar to context shifts in the way that they are defined and passed to subdialogs. The difference is that rather than returning control to the dialog module where they are defined, they initiate a new subdialog which is takes control of the conversation. Once the digression subdialog is completed, control returns to the module that had control before the digression.
- A confirmation module confirms an answer and often occurs often within a voice application, and may be required for other dialog strategies. When a context shift occurs, for example, the system might require confirmation from the user before the shift is executed. The author of the dialog application can create a single dialog module, or use and existing dialog module for all of these tasks. The module that will be used is indicated at the application level, and will be used by all occasions of confirmation throughout the application. Confirmation occurs when certain data supplied by the user requires explicit confirmation (no matter what confidence level the NLU has returned). This might be done by requesting that the user choose between two tasks, for example.
- Correction occurs when the user corrects or changes information (thus requiring the system to loop back to a previous state or pursue another kind of decision path). Multi-input occurs when the user volunteers more input than they have been prompted to supply (and the system captures this info so that later the user only needs to verify information already provided). Reprompting occurs when the DM application presents a caller with a repeat prompt using slightly different wording.
- When the DM author wishes to uses any of these patterns, the control structure is already in place so they can focus on the parameters of the structure that are specific to their application. Context shifts, for example, require a way to ensure that certain key phrases (such as “quit”, “start over”, or a complete change of topic) or conditions will trigger an application specific response, even when a pre-existing dialog definition is being re-used.
- Support of a Context Shift dialog pattern allows the application to react to abrupt changes in the flow of conversation with a user. A context shift is one of the more tedious types of transitions to encode throughout an entire application, and it typically prevents reuse of existing subdialogs that do not include it. The context shift mechanism defines the transition for the entire dialog, and passes it on to subdialogs as well. This means that even if the developer is using a standardized subdialog for, for instance, gathering input, this transition will still be active in the unmodified subdialog.
- A context shift is based on two pieces of information: the input which triggers the shift, and the name of the state where the shift goes. When a subdialog is created, it inherits the context shifts of its parent dialog. If a shift is fired, the subdialog returns a message that a shift has occurred and the parent dialog is set to the state described by the shift. The only time that a subdialog does not inherit a context shift is when it already has a shift defined for the same trigger concept.
- In the digression idiom, the application must not only respect key phrases or conditions (such as “explain” or “help”), but also be able to restore the previous state of the dialog when it is complete. These patterns do not have to be explained by the author, they are already understood by the system. This makes it possible for them to be used without having to specify the application-independent aspects of the feature.
-
FIG. 6 illustrates exemplary steps that are performed in the method embodiment of the invention. As shown, the developer may implement the dialog strategy by selecting the top level flow controller type (602) as determined by the type of application. Although there might be applications that require a Clarification or Rules FC as the top level dialog, the RTN FC is generally the appropriate type of top level dialog for most applications. Because RTNs are general state machines, they are usually the right FC for a call flow application. Next, the developer breaks the application down into parts that require different FCs below that top level (604). Based on types of subdialogs the developer intends to write, for example, one may want to incorporate tree logic and/or a rules-based module nested within the states transition module. The developer checks for available subdialogs and selects reusable subdialogs for each application part (606). For example, the reusable InputSD and other subdialogs will be in a developer's library. Thus there are a variety of application parts below the top level flow controller that may be determined Where a subdialog is not available, the method comprises developing a subdialog for each application part that does not have an available subdialog (608). Once available subdialogs and developed subdialogs are selected, the developer will test and deploy the spoken dialog service using the selected top-level flow controller, selected subdialogs and developed subdialogs (610). -
FIG. 2 represents adialog manager 202 with a loadedflow controller 208 for a top level dialog from anXML data file 204. Anotherflow controller 210 is loaded from an XML application data file 206. The use of multiple flow controllers provides in the present invention an encapsulated, reusable and customizable approach to a spoken dialog. This provides an interface definition for a fully encapsulated dialog logic module and its interaction with other FCs. - The DM application framework with modular logic (DMML) permits the system developer to choose dialog strategy appropriate to the service domain and combine strategies as appropriate. Several concepts make this workable. These include the FC and local context, introduced above.
- The local context is applied within each
FC - Other dialog patterns may also be implemented using the modular approach disclosed herein. For example, a correction pattern can be implemented to handle the situation where the user corrects or changes information previously given. A multi-input pattern can be handled where the user volunteers more information then he or she has been asked to give. Further, in some cases, explicit confirmation of input is required no matter the NLU confidence.
- The multiple flow controllers can provide interchange between each flow controller using a recursive transition network (RTN) which involves storing and manipulating states, transitions and actions between various FCs. In one aspect of the invention, the modular flow controllers are implemented in a rule-based manner where actions are based on certain criteria, a silent count and rejection count are maintained, and slot values are filled or unfilled.
- The subdialogs that are initiated (see 210
FIG. 2 ) may be initialized by a parent dialog before activation. An input is sent to a subdialog until its use is complete. Results can be retrieved by a parent dialog and context shifts can also return flow control to a parent dialog. The process of encapsulation involves loading each FC into the dialog manager application separately. In this regard, the same protocol is used for invocation and for communicating and switching flow control among FCs. The context shifts allow the control to pass between different types of FCs. - Finally, context shifts permit abrupt transitions between FCs.
FIG. 7 illustrates a method aspect of the invention associated with managing context shifts between FCs. These transitions are defined in a manner that permits each FC to describe a destination for the jump in a customized manner, and to pass the definition of this jump to FCs of other types. This feature allows the content author to seamlessly use diverse systems of dialog logic in combination. Internally, the DMML maintains a stack of FCs, for example a first FC and a second FC. While the spoken dialog is being managed by a current FC, the system will receive input associated with the user speech and provide responses according to the particular context of the FC. In this dialog, the user may want to switch contexts of the conversation (e.g., from account balance information to a transaction between accounts). The spoken dialog system will then receive input associated with the user speech that includes information indicating that a context switch is desired by the user (702). When the current FC invokes a second FC, the second FC is added to the stack and will be the recipient of all new inputs from the spoken dialog until it has relinquished control to the parent or first FC. Context shifts are inherited by the second FC, and values may be copied from the local context of the first FC. When new input is received, it is passed to the most recent FC, where it is first compared to at least one context shift (704). The context shifts may be stored within a table. If any of the context shifts are activated, control is passed to the new FC indicated by the context shift, and the FC is set to the state that the shift describes (706). If no context shift is activated, control passes to the logic of the first FC (708). The current FC can return control to a previous FC whenever its logic dictates. - The discussion now returns to the development process. As the developer reviews the library of available subdialogs, the developer may determine whether a new subdialog needs to be developed. The subdialog strategy will have been largely determined by the SLU concepts generated during the design phase. General discourse concepts such as YES and NO are available (for example, the developer will see that the basic Input Subdialog uses discourse_yes and discourse_no for confirmation if the SLU confidence score is too low.). Other pre-assigned prompts for use in special circumstances may be associated with the reusable input subdialogs. Specific subdialogs, like BILLING, CREDIT_CARD, and so forth are available. The developer lists all the prompts that may be used. Note that the RTN actions can be completed with the real actions defined as prompts and grammar activation in the call flow. While the developer is working in the keyboard mode (using the Florence Command Line tool) during development, he or she will just input the expected text for the prompt. Later, when the system is ready to be deployed on the NLS platform the developer will need VoiceXML snippets with the actual prompt definitions (either pre-recorded prompts pointers or text-to-speech commands).
- The developer determines what customization the application requires (i.e., additional java for customized algorithms) and creates application files (an application configuration data file, a top level dialog data file and any necessary subdialog data files) based on a dialog strategy. If necessary, the developer creates an output processing template (or adapt one of the sample templates provided in the Florence or other developer's Toolkit) to format the output for the application. Most DM applications include a template file that functions as the output processor, formatting application output as XHTML, XML or VoiceXML code. When a template is included among the application files, the application's configuration data file element is given a template attribute. The value of that attribute is the template filename (eg, template=“VoiceXMLTemplate.vxml”). Florence's simple output processor may be used when it is appropriate such as when plain text is acceptable application output—for example, when the application is being developed, debugged or tested using a command line tool to provide text input and text output. (In this case, template=“text” is used instead of a template filename.)
- Next is discussed the details of building the DM application files, including use of the Florence XML schema and application file templates. Reuse of subdialogs (from other existing Florence applications or other applications) is also covered.
FIG. 5A illustrates a reusable subdialog. In this case, thereusable subdialog 500 is an input flow controller. The states include an S1 state for receiving input from the user. S0 is an input prompt state. This particular group of states illustrates how to handle silence in theinput FC 500. If silence is heard, the transition C1 takes the flow to state S2 which increments the silence count and returns the flow to the get input state S1 with a silent count parameter. This interaction continues if more silence is heard until the silent count reaches a threshold value, represented by a C2 transition to the fail state. If input is received appropriately, then the flow may transition to the done state. In this example, error prompt and the silent count threshold values may be parameters transmitted to this RTN subdialog. -
FIG. 5B illustrates a more complex RTNreusable subdialog 502. In this case, the input prompt S0 transitions to state S1 which receives the user input. This subdialog handles silence, rejection, a wrong category and a confirmation interaction with the user. If silence is heard, the C4 transition goes to state S5 which increments the SilentCount parameter. If a wrong category is received, a wrong category transition C6 transitions to state S7 which increments a WrongCategoryCount parameter and returns to state S1. A rejection input results in a C5 rejection action transition to state S6 which increments a RejectionCount parameter. As these parameters each reach a threshold value, then the following transitions may bring the flow to the fail state: C7 for a SilenceFailAction; C8 for a RejectionFailAction; and C9 for a WrongCategoryAction transition. If user input is received at state S1, that requires confirmation, the flow transitions to state S2 that performs a confirmation interaction with the user, represented by states S3 and S4 and transitions C1, C2, and C3, which transition to either the fail state or the done state. In this manner, the spoken dialog system can confirm user input. - Note that the top-level dialog of an application must be identified in a <dialogfile> element in an application configuration data file. All other dialogs in an application are considered subdialogs that can be called from that top-level dialog—or from other subdialogs in the application. Any subdialogs that will be called must be declared in <dialogfile> tags within the <subdialogs> element in the code of the calling dialog file.
- Building an application configuration data file is discussed next. A Florence application's configuration file provides key information, such as what the top-level dialog of the application is, what output processor is used, what NLU engine is used, what types of debugging information and log messages will be captured, and so forth. The structure and content of an application configuration data file based on the config.fxml template is generally as follows:
-
<xml> <fxml> <configuration> <dialogfile/> <nlu/> <output/> </configuration> </fxml> </xml> - The fxml element tag, which is the parent for all other FXML tags used, establishes this as a Florence application file using the FXML schema. The configuration tag establishes the file as an application configuration data file type and contains child elements used to define specific configuration data. The dialogfile tag identifies the top-level dialog of this application. The NLU tag specifies the location of input data by providing host and port number for the NLU (ie, the NLU engine which is to supply the compiled and interpreted data generated from the application user's natural language input). The output tag identifies the type of output expected from this DM application and the template, if any, that will format the output.
- In a typical voice application, this would probably be a VXML template used to format the DM output as VXML. That VXML would be processed by the Florence SLG before and then sent to the Natural Voices TTS engine or prompt player, which would generate a spoken response for the application user.
- The process of building a global context file is discussed next. The global context file is specified by path and filename in an application's configuration data, using the globals= attribute of the <configuration> element. This allows global context to be accessed by any dialog or subdialog in the application. When the DM engine cannot find a variable in the local context of the currently active dialog or subdialog, Florence will look for it in the global context file specified by the application's configuration file.
- Global context is built using <dictionary> and <var> elements in the same manner as local context built within a dialog file, however global variable definitions are grouped in a separate FXML file. Global context functions in the same way as local context, with one exception: the NLU results will only be stored locally.
- The structure and content of a global context file based on the global.fxml template is generally as follows:
-
<xml> <fxml> <global> <var/> <array/> <dictionary/> </global> </fxml> </xml> - The <var>, <array> and <dictionary> tags used in a global context file have name= and expr= attributes and can also contain nested <var> and <value> tags. Thus, in practice, a global context file used by an application might look more like the following:
-
<xml> <fxml> <global> <var name=“globalTest” expr=“2” /> <var name=“globalIncrementTest” expr=“0” /> <array name=“globalNames”> <value expr=“1.3.1 Action without arguments but with global context array.” /> </array> <dictionary name=“globalDictionaryTest”> <var name=“test” expr=“1.4.1 Action without arguments but with global context array.”/> </dictionary> </global> </fxml> </xml> - As with all Florence files, the fxml element tag establishes this as a Florence application file using the FXML schema and serves as a container for all other FXML tags used in this file. The global tag establishes the file as a global context file type and contains child elements used to define specific variables and parameters. The var tag is used here to specify global context variables. The array tag is used here to define a global context array. The dictionary tag is used here for a look-up list of global variable names.
- Next, we discuss building an RTN FC Dialog File. A Florence application's top-level dialog is most often a dialog based on the Recursive Transition Network (RTN) flow controller (FC) implementation. RTN dialogs are based on the concepts of states and transitions between states.
- As with all Florence files, the fxml element tag establishes this as a Florence application file using the FXML schema and serves as a container for all other FXML tags used in this file. The rtn tag establishes this as a dialog based on the RTN FC and contains all the child elements used to build the RTN dialog, including tags to: local to describe local context, subdialogs to identify subdialogs, actiondefs to define actions, states to specify states (with associated instructions), transitions to specify transitions (with associated actions), contextshift to identify context shifts, and chronoshift to identify chronoshifts.
- Next is discussed the process of building an output processing template. Many simple applications can use the output processor that's built into Florence, but most complex applications will require their own output processing template—ie, a template to format Florence output. A few different output processing templates are provided with the Florence sample applications. These templates include typical elements, such as confidence level and log level values, identification of the ASR engine being used, and so forth. The best way to understand how to build an output processing template is to examine these models. They may be adapted to the needs of a new application.
- The Florence DM engine's built-in output processor uses an application's dialog components in conjunction with its output template to prepare appropriate output in response to user input. In a VoiceTone spoken dialog application such as a customer care system, this output is what will ultimately generate the response to be returned to the customer. This output can take the form of simple text, but most typically the output is formatted by the application's output processor—a VoiceXML template—as VoiceXML code containing speech text prompts. Those speech text prompts are then used by the Natural Voices TTS engine to generate the system's spoken response to the customer.
- Two components control the content of output from Florence: the Output Processor and the Action object. The Output Processor formats Florence output into text, VoiceXML, or whatever other type of string output it has been specialized to provide. The content comes from an Action object in the currently active dialog. For the Output Processor to work correctly, it must be able to get the content it needs from the Action object. This creates a strong coupling between these two components; they will usually be created in pairs.
- For VoiceXML applications, the <output> element defined in an application's configuration data file must specify a VXML template (such as the VoiceXMLTemplate.vxml file that is supplied with the Florence examples). The VXML template not only uses the text of an action, which is part of a normal action definition, but it can also use arbitrary blocks of VXML code which have been associated with the action.
- Output formats are discussed next. Although an output processor can be devised to provide many kinds of string output, the most typical output formats are simple text and VoiceXML: (1) Simple Text Output: For simple text output from an application, specify “text” as the value of the template attribute of the <output> element in the application's configuration data file. The <actiondef> element in a dialog usually includes a text attribute. The value of this attribute determines the output text created by this action through a simple text output processor (ie, the literal text that appears as the value is what will be output). (2) VoiceXML Output: In order to use a VXML template for Florence output, the developer may desire to add a template attribute to the element in the application configuration data file. The value of the template attribute is the pathname (relative to the data directory) of the VXML template file the developer intends to use. The text of this file will be returned every time an action is taken by Florence.
- Next is discussed the process of adapting reusable subdialogs for an application. The method of developing a dialog manager preferably includes a step of selecting an available reusable subdialog for each application part. The example reusable dialog is the input subdialog (referred to as the InputSD). The input subdialog is a reusable dialog for collecting input from the user. It is capable of handling silences, rejections, low confidence NLU results, and explicit confirmation and it can be configured with custom prompts and patience levels for each invocation. This section describes how to configure the InputSD, what behavior to expect from it, and how to retrieve results from it. It also includes an example of how to use the InputSD.
- The InputSD uses the actions copied to it when it is invoked to handle specific problems that arise during the input process. When a problem arises, the InputSD checks to see if its patience for that sort of problem has been exceeded. If it has, then the dialog fails and ends. If its patience has not been exceeded, the InputSD plays a prompt from the list of prompts that have been sent to the subdialog to apply to special circumstances.
- The special circumstances are silence, rejection, and low-confidence NLU value. In the case of an NLU value returned with a low confidence score, the user is given the opportunity to confirm the value with a yes or no answer (unless the dialog is already trying to get a yes/no value). It is also possible to request that the dialog always confirm a value before it is returned. The InputSD handles this in a manner similar to the handling of low-confidence values.
- Input values are the local variables that can be configured when the InputSD is invoked. These variables are set using <set> in an <entersubdialog> element. Any prompts that will be used in the InputSD must also be copied in this instruction set with a <copy> element. See the sample code at the end of this section for an example.
- Allowed input values include: InputPrompt—this is the name of the prompt to play when the InputSD begins; YN—set this to “true” if the dialog is being invoked to collect a yes or no response (it defaults to “false”); YvalueName—this is the value that the dialog will recognize as “yes” (it defaults to “discourse_yes”); NvalueName—this is the value that the dialog will recognize as “no” (it defaults to “discourse_no”); SilenceCategory—this is the value that the dialog will recognize as a silence (it has no default); RejectCategory—this is the value that the dialog will recognize as a rejection (it has no default); ConfidenceThreshold—the input must have a confidence level above this threshold (it defaults to 0); and ExplicitConfirm—if this dialog must always confirm responses, set this to “true” (it defaults to “false”).
- Each of the following variables describes how many times the dialog will tolerate a particular type of input failure before failing. Each defaults to 0: SilencePatience; RejectionPatience; ConfidencePatience—this applies to low-confidence, unconfirmed inputs; and confirmPatience—this is the number of times an explicit confirmation can receive a “no” answer.
- The following variables are action names. Local context array variables (the <array> elements within the <local> element of an RTN FC dialog file) must be copied into these values. There must also be an action for each of the names given, and each of these actions must be copied using the copy action instruction (<copy>). The InputSD iterates over each of these sets of actions for a particular type of input situation. If the counter value of the iteration exceeds the size of the array, the last value will be used again: SilenceActions; RejectionActions; ConfidenceActions—this action prompts the user for a yes/no confirmation of a low-confidence input; ConfirmRequestActions—this action prompts the user for a yes/no explicit confirmation; ConfirmActions—these prompts are called if the explicit confirmation or a low-confidence confirm gets a “no” response.
- The following failure actions occur when the patience for a particular situation is exceeded. These variables each contain the name of an action, which must be copied separately with copy action instruction (<copy>): SilenceFailAction; RejectionFailAction; ConfidenceFailAction; and ExplicitConfirmFailAction.
- These are the local variables that can be retrieved when the InputSD is finished: RetumConcept—the NLU concept that was the InputSD received; RetumValue —the text received by the InputSD; RetumConfidence—the confidence score of the result; result—the actual NLU result; and Success—true or false. These variables are retrieved using SetInstruction in an instruction set with subDialogInstructions set to “true” and enterInstructions set to “false”.
- Embodiments within the scope of the present invention may also include computer-readable media for carrying or having computer-executable instructions or data structures stored thereon. Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer-executable instructions or data structures. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or combination thereof) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such connection is properly termed a computer-readable medium. Combinations of the above should also be included within the scope of the computer-readable media.
- Computer-executable instructions include, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. Computer-executable instructions also include program modules that are executed by computers in stand-alone or network environments. Generally, program modules include routines, programs, objects, components, and data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of the program code means for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps.
- Those of skill in the art will appreciate that other embodiments of the invention may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Embodiments may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
- Although the above description may contain specific details, they should not be construed as limiting the claims in any way. Other configurations of the described embodiments of the invention are part of the scope of this invention. Although AT&T's Florence framework and other speech products are discussed, the present invention is certainly not limited to any such specific method or product. Furthermore, the invention is not limited to a specific standard or protocol in developing speech applications. It may be applied to existing speech platforms and used in connection with industry standards such as VXML and SALT to address complex dialog strategies. Accordingly, the appended claims and their legal equivalents should only define the invention, rather than any specific examples given.
Claims (20)
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US14/261,549 US9257116B2 (en) | 2003-05-15 | 2014-04-25 | System and dialog manager developed using modular spoken-dialog components |
US15/013,040 US20160154788A1 (en) | 2003-05-15 | 2016-02-02 | System and dialog manager developed using modular spoken-dialog components |
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US47082403P | 2003-05-15 | 2003-05-15 | |
US10/790,495 US7421393B1 (en) | 2004-03-01 | 2004-03-01 | System for developing a dialog manager using modular spoken-dialog components |
US12/201,423 US8473299B2 (en) | 2004-03-01 | 2008-08-29 | System and dialog manager developed using modular spoken-dialog components |
US13/926,366 US8725517B2 (en) | 2003-05-15 | 2013-06-25 | System and dialog manager developed using modular spoken-dialog components |
US14/261,549 US9257116B2 (en) | 2003-05-15 | 2014-04-25 | System and dialog manager developed using modular spoken-dialog components |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/926,366 Continuation US8725517B2 (en) | 2003-05-15 | 2013-06-25 | System and dialog manager developed using modular spoken-dialog components |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/013,040 Continuation US20160154788A1 (en) | 2003-05-15 | 2016-02-02 | System and dialog manager developed using modular spoken-dialog components |
Publications (2)
Publication Number | Publication Date |
---|---|
US20140324427A1 true US20140324427A1 (en) | 2014-10-30 |
US9257116B2 US9257116B2 (en) | 2016-02-09 |
Family
ID=39718462
Family Applications (5)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/790,495 Active 2026-05-07 US7421393B1 (en) | 2003-05-15 | 2004-03-01 | System for developing a dialog manager using modular spoken-dialog components |
US12/201,423 Active 2025-10-12 US8473299B2 (en) | 2003-05-15 | 2008-08-29 | System and dialog manager developed using modular spoken-dialog components |
US13/926,366 Expired - Lifetime US8725517B2 (en) | 2003-05-15 | 2013-06-25 | System and dialog manager developed using modular spoken-dialog components |
US14/261,549 Expired - Lifetime US9257116B2 (en) | 2003-05-15 | 2014-04-25 | System and dialog manager developed using modular spoken-dialog components |
US15/013,040 Abandoned US20160154788A1 (en) | 2003-05-15 | 2016-02-02 | System and dialog manager developed using modular spoken-dialog components |
Family Applications Before (3)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US10/790,495 Active 2026-05-07 US7421393B1 (en) | 2003-05-15 | 2004-03-01 | System for developing a dialog manager using modular spoken-dialog components |
US12/201,423 Active 2025-10-12 US8473299B2 (en) | 2003-05-15 | 2008-08-29 | System and dialog manager developed using modular spoken-dialog components |
US13/926,366 Expired - Lifetime US8725517B2 (en) | 2003-05-15 | 2013-06-25 | System and dialog manager developed using modular spoken-dialog components |
Family Applications After (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US15/013,040 Abandoned US20160154788A1 (en) | 2003-05-15 | 2016-02-02 | System and dialog manager developed using modular spoken-dialog components |
Country Status (1)
Country | Link |
---|---|
US (5) | US7421393B1 (en) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9257116B2 (en) * | 2003-05-15 | 2016-02-09 | At&T Intellectual Property Ii, L.P. | System and dialog manager developed using modular spoken-dialog components |
US10957310B1 (en) | 2012-07-23 | 2021-03-23 | Soundhound, Inc. | Integrated programming framework for speech and text understanding with meaning parsing |
US11295730B1 (en) | 2014-02-27 | 2022-04-05 | Soundhound, Inc. | Using phonetic variants in a local context to improve natural language understanding |
Families Citing this family (223)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8645137B2 (en) | 2000-03-16 | 2014-02-04 | Apple Inc. | Fast, language-independent method for user authentication by voice |
ITFI20010199A1 (en) | 2001-10-22 | 2003-04-22 | Riccardo Vieri | SYSTEM AND METHOD TO TRANSFORM TEXTUAL COMMUNICATIONS INTO VOICE AND SEND THEM WITH AN INTERNET CONNECTION TO ANY TELEPHONE SYSTEM |
US7398209B2 (en) | 2002-06-03 | 2008-07-08 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US7693720B2 (en) | 2002-07-15 | 2010-04-06 | Voicebox Technologies, Inc. | Mobile systems and methods for responding to natural language speech utterance |
US7412393B1 (en) * | 2004-03-01 | 2008-08-12 | At&T Corp. | Method for developing a dialog manager using modular spoken-dialog components |
US7640160B2 (en) | 2005-08-05 | 2009-12-29 | Voicebox Technologies, Inc. | Systems and methods for responding to natural language speech utterance |
US7620549B2 (en) * | 2005-08-10 | 2009-11-17 | Voicebox Technologies, Inc. | System and method of supporting adaptive misrecognition in conversational speech |
US7949529B2 (en) | 2005-08-29 | 2011-05-24 | Voicebox Technologies, Inc. | Mobile systems and methods of supporting natural language human-machine interactions |
US8677377B2 (en) | 2005-09-08 | 2014-03-18 | Apple Inc. | Method and apparatus for building an intelligent automated assistant |
US9009046B1 (en) * | 2005-09-27 | 2015-04-14 | At&T Intellectual Property Ii, L.P. | System and method for disambiguating multiple intents in a natural language dialog system |
US9318108B2 (en) | 2010-01-18 | 2016-04-19 | Apple Inc. | Intelligent automated assistant |
US8073681B2 (en) | 2006-10-16 | 2011-12-06 | Voicebox Technologies, Inc. | System and method for a cooperative conversational voice user interface |
US7818176B2 (en) | 2007-02-06 | 2010-10-19 | Voicebox Technologies, Inc. | System and method for selecting and presenting advertisements based on natural language processing of voice-based input |
US8977255B2 (en) | 2007-04-03 | 2015-03-10 | Apple Inc. | Method and system for operating a multi-function portable electronic device using voice-activation |
US9053089B2 (en) | 2007-10-02 | 2015-06-09 | Apple Inc. | Part-of-speech tagging using latent analogy |
US8140335B2 (en) | 2007-12-11 | 2012-03-20 | Voicebox Technologies, Inc. | System and method for providing a natural language voice user interface in an integrated voice navigation services environment |
US10002189B2 (en) | 2007-12-20 | 2018-06-19 | Apple Inc. | Method and apparatus for searching using an active ontology |
US9330720B2 (en) | 2008-01-03 | 2016-05-03 | Apple Inc. | Methods and apparatus for altering audio output signals |
US8065143B2 (en) | 2008-02-22 | 2011-11-22 | Apple Inc. | Providing text input using speech data and non-speech data |
US8996376B2 (en) | 2008-04-05 | 2015-03-31 | Apple Inc. | Intelligent text-to-speech conversion |
US10496753B2 (en) * | 2010-01-18 | 2019-12-03 | Apple Inc. | Automatically adapting user interfaces for hands-free interaction |
US9305548B2 (en) | 2008-05-27 | 2016-04-05 | Voicebox Technologies Corporation | System and method for an integrated, multi-modal, multi-device natural language voice services environment |
US8589161B2 (en) | 2008-05-27 | 2013-11-19 | Voicebox Technologies, Inc. | System and method for an integrated, multi-modal, multi-device natural language voice services environment |
US8464150B2 (en) | 2008-06-07 | 2013-06-11 | Apple Inc. | Automatic language identification for dynamic text processing |
US20100030549A1 (en) | 2008-07-31 | 2010-02-04 | Lee Michael M | Mobile device having human language translation capability with positional feedback |
US8768702B2 (en) | 2008-09-05 | 2014-07-01 | Apple Inc. | Multi-tiered voice feedback in an electronic device |
US8898568B2 (en) | 2008-09-09 | 2014-11-25 | Apple Inc. | Audio user interface |
US8712776B2 (en) | 2008-09-29 | 2014-04-29 | Apple Inc. | Systems and methods for selective text to speech synthesis |
US8676904B2 (en) | 2008-10-02 | 2014-03-18 | Apple Inc. | Electronic devices with voice command and contextual data processing capabilities |
WO2010067118A1 (en) | 2008-12-11 | 2010-06-17 | Novauris Technologies Limited | Speech recognition involving a mobile device |
US8224653B2 (en) * | 2008-12-19 | 2012-07-17 | Honeywell International Inc. | Method and system for operating a vehicular electronic system with categorized voice commands |
US8862252B2 (en) | 2009-01-30 | 2014-10-14 | Apple Inc. | Audio user interface for displayless electronic device |
US8326637B2 (en) | 2009-02-20 | 2012-12-04 | Voicebox Technologies, Inc. | System and method for processing multi-modal device interactions in a natural language voice services environment |
US8380507B2 (en) | 2009-03-09 | 2013-02-19 | Apple Inc. | Systems and methods for determining the language to use for speech generated by a text to speech engine |
US9858925B2 (en) | 2009-06-05 | 2018-01-02 | Apple Inc. | Using context information to facilitate processing of commands in a virtual assistant |
US10241752B2 (en) | 2011-09-30 | 2019-03-26 | Apple Inc. | Interface for a virtual digital assistant |
US10540976B2 (en) | 2009-06-05 | 2020-01-21 | Apple Inc. | Contextual voice commands |
US10706373B2 (en) | 2011-06-03 | 2020-07-07 | Apple Inc. | Performing actions associated with task items that represent tasks to perform |
US10241644B2 (en) | 2011-06-03 | 2019-03-26 | Apple Inc. | Actionable reminder entries |
US9431006B2 (en) | 2009-07-02 | 2016-08-30 | Apple Inc. | Methods and apparatuses for automatic speech recognition |
US9502025B2 (en) * | 2009-11-10 | 2016-11-22 | Voicebox Technologies Corporation | System and method for providing a natural language content dedication service |
US9171541B2 (en) | 2009-11-10 | 2015-10-27 | Voicebox Technologies Corporation | System and method for hybrid processing in a natural language voice services environment |
US8682649B2 (en) | 2009-11-12 | 2014-03-25 | Apple Inc. | Sentiment prediction from textual data |
US8311838B2 (en) | 2010-01-13 | 2012-11-13 | Apple Inc. | Devices and methods for identifying a prompt corresponding to a voice input in a sequence of prompts |
US8381107B2 (en) | 2010-01-13 | 2013-02-19 | Apple Inc. | Adaptive audio feedback system and method |
US10553209B2 (en) | 2010-01-18 | 2020-02-04 | Apple Inc. | Systems and methods for hands-free notification summaries |
US10276170B2 (en) | 2010-01-18 | 2019-04-30 | Apple Inc. | Intelligent automated assistant |
US10705794B2 (en) | 2010-01-18 | 2020-07-07 | Apple Inc. | Automatically adapting user interfaces for hands-free interaction |
US10679605B2 (en) | 2010-01-18 | 2020-06-09 | Apple Inc. | Hands-free list-reading by intelligent automated assistant |
US8682667B2 (en) | 2010-02-25 | 2014-03-25 | Apple Inc. | User profiling for selecting user specific voice input processing information |
US8713021B2 (en) | 2010-07-07 | 2014-04-29 | Apple Inc. | Unsupervised document clustering using latent semantic density analysis |
US8719006B2 (en) | 2010-08-27 | 2014-05-06 | Apple Inc. | Combined statistical and rule-based part-of-speech tagging for text-to-speech synthesis |
US8719014B2 (en) | 2010-09-27 | 2014-05-06 | Apple Inc. | Electronic device with text error correction based on voice recognition data |
US10515147B2 (en) | 2010-12-22 | 2019-12-24 | Apple Inc. | Using statistical language models for contextual lookup |
US10762293B2 (en) | 2010-12-22 | 2020-09-01 | Apple Inc. | Using parts-of-speech tagging and named entity recognition for spelling correction |
US8781836B2 (en) | 2011-02-22 | 2014-07-15 | Apple Inc. | Hearing assistance system for providing consistent human speech |
US9262612B2 (en) | 2011-03-21 | 2016-02-16 | Apple Inc. | Device access using voice authentication |
US10672399B2 (en) | 2011-06-03 | 2020-06-02 | Apple Inc. | Switching between text data and audio data based on a mapping |
US10057736B2 (en) | 2011-06-03 | 2018-08-21 | Apple Inc. | Active transport based notifications |
US8812294B2 (en) | 2011-06-21 | 2014-08-19 | Apple Inc. | Translating phrases from one language into another using an order-based set of declarative rules |
US8706472B2 (en) | 2011-08-11 | 2014-04-22 | Apple Inc. | Method for disambiguating multiple readings in language conversion |
US8994660B2 (en) | 2011-08-29 | 2015-03-31 | Apple Inc. | Text correction processing |
US8762156B2 (en) | 2011-09-28 | 2014-06-24 | Apple Inc. | Speech recognition repair using contextual information |
US10134385B2 (en) | 2012-03-02 | 2018-11-20 | Apple Inc. | Systems and methods for name pronunciation |
US9483461B2 (en) | 2012-03-06 | 2016-11-01 | Apple Inc. | Handling speech synthesis of content for multiple languages |
US9280610B2 (en) | 2012-05-14 | 2016-03-08 | Apple Inc. | Crowd sourcing information to fulfill user requests |
US8775442B2 (en) | 2012-05-15 | 2014-07-08 | Apple Inc. | Semantic search using a single-source semantic model |
US10417037B2 (en) | 2012-05-15 | 2019-09-17 | Apple Inc. | Systems and methods for integrating third party services with a digital assistant |
US9679568B1 (en) | 2012-06-01 | 2017-06-13 | Google Inc. | Training a dialog system using user feedback |
US9123338B1 (en) | 2012-06-01 | 2015-09-01 | Google Inc. | Background audio identification for speech disambiguation |
US10019994B2 (en) | 2012-06-08 | 2018-07-10 | Apple Inc. | Systems and methods for recognizing textual identifiers within a plurality of words |
US9721563B2 (en) | 2012-06-08 | 2017-08-01 | Apple Inc. | Name recognition system |
US9495129B2 (en) | 2012-06-29 | 2016-11-15 | Apple Inc. | Device, method, and user interface for voice-activated navigation and browsing of a document |
US9576574B2 (en) | 2012-09-10 | 2017-02-21 | Apple Inc. | Context-sensitive handling of interruptions by intelligent digital assistant |
US9547647B2 (en) | 2012-09-19 | 2017-01-17 | Apple Inc. | Voice-based media searching |
US8935167B2 (en) | 2012-09-25 | 2015-01-13 | Apple Inc. | Exemplar-based latent perceptual modeling for automatic speech recognition |
US9070366B1 (en) | 2012-12-19 | 2015-06-30 | Amazon Technologies, Inc. | Architecture for multi-domain utterance processing |
CN113470641B (en) | 2013-02-07 | 2023-12-15 | 苹果公司 | Voice trigger of digital assistant |
US10572476B2 (en) | 2013-03-14 | 2020-02-25 | Apple Inc. | Refining a search based on schedule items |
US9733821B2 (en) | 2013-03-14 | 2017-08-15 | Apple Inc. | Voice control to diagnose inadvertent activation of accessibility features |
US10642574B2 (en) | 2013-03-14 | 2020-05-05 | Apple Inc. | Device, method, and graphical user interface for outputting captions |
US9977779B2 (en) | 2013-03-14 | 2018-05-22 | Apple Inc. | Automatic supplementation of word correction dictionaries |
US10652394B2 (en) | 2013-03-14 | 2020-05-12 | Apple Inc. | System and method for processing voicemail |
US9368114B2 (en) | 2013-03-14 | 2016-06-14 | Apple Inc. | Context-sensitive handling of interruptions |
US11151899B2 (en) | 2013-03-15 | 2021-10-19 | Apple Inc. | User training by intelligent digital assistant |
US10748529B1 (en) * | 2013-03-15 | 2020-08-18 | Apple Inc. | Voice activated device for use with a voice-based digital assistant |
WO2014144949A2 (en) | 2013-03-15 | 2014-09-18 | Apple Inc. | Training an at least partial voice command system |
CN112230878B (en) | 2013-03-15 | 2024-09-27 | 苹果公司 | Context-dependent processing of interrupts |
WO2014144579A1 (en) | 2013-03-15 | 2014-09-18 | Apple Inc. | System and method for updating an adaptive speech recognition model |
US20140358538A1 (en) * | 2013-05-28 | 2014-12-04 | GM Global Technology Operations LLC | Methods and systems for shaping dialog of speech systems |
WO2014197334A2 (en) | 2013-06-07 | 2014-12-11 | Apple Inc. | System and method for user-specified pronunciation of words for speech synthesis and recognition |
WO2014197336A1 (en) | 2013-06-07 | 2014-12-11 | Apple Inc. | System and method for detecting errors in interactions with a voice-based digital assistant |
US9582608B2 (en) | 2013-06-07 | 2017-02-28 | Apple Inc. | Unified ranking with entropy-weighted information for phrase-based semantic auto-completion |
WO2014197335A1 (en) | 2013-06-08 | 2014-12-11 | Apple Inc. | Interpreting and acting upon commands that involve sharing information with remote devices |
US10176167B2 (en) | 2013-06-09 | 2019-01-08 | Apple Inc. | System and method for inferring user intent from speech inputs |
KR101772152B1 (en) | 2013-06-09 | 2017-08-28 | 애플 인크. | Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant |
CN105265005B (en) | 2013-06-13 | 2019-09-17 | 苹果公司 | System and method for the urgent call initiated by voice command |
CN105453026A (en) | 2013-08-06 | 2016-03-30 | 苹果公司 | Auto-activating smart responses based on activities from remote devices |
US10296160B2 (en) | 2013-12-06 | 2019-05-21 | Apple Inc. | Method for extracting salient dialog usage from live data |
US9817813B2 (en) * | 2014-01-08 | 2017-11-14 | Genesys Telecommunications Laboratories, Inc. | Generalized phrases in automatic speech recognition systems |
US9620105B2 (en) | 2014-05-15 | 2017-04-11 | Apple Inc. | Analyzing audio input for efficient speech and music recognition |
KR102069700B1 (en) * | 2014-05-20 | 2020-01-23 | 한국전자통신연구원 | Automatic speech recognition system for replacing specific domain search network, mobile device and method thereof |
US10592095B2 (en) | 2014-05-23 | 2020-03-17 | Apple Inc. | Instantaneous speaking of content on touch devices |
US9502031B2 (en) | 2014-05-27 | 2016-11-22 | Apple Inc. | Method for supporting dynamic grammars in WFST-based ASR |
US9430463B2 (en) | 2014-05-30 | 2016-08-30 | Apple Inc. | Exemplar-based natural language processing |
US10170123B2 (en) | 2014-05-30 | 2019-01-01 | Apple Inc. | Intelligent assistant for home automation |
US10078631B2 (en) | 2014-05-30 | 2018-09-18 | Apple Inc. | Entropy-guided text prediction using combined word and character n-gram language models |
US9715875B2 (en) | 2014-05-30 | 2017-07-25 | Apple Inc. | Reducing the need for manual start/end-pointing and trigger phrases |
US9633004B2 (en) | 2014-05-30 | 2017-04-25 | Apple Inc. | Better resolution when referencing to concepts |
WO2015184186A1 (en) | 2014-05-30 | 2015-12-03 | Apple Inc. | Multi-command single utterance input method |
US9785630B2 (en) | 2014-05-30 | 2017-10-10 | Apple Inc. | Text prediction using combined word N-gram and unigram language models |
US9842101B2 (en) | 2014-05-30 | 2017-12-12 | Apple Inc. | Predictive conversion of language input |
US9734193B2 (en) | 2014-05-30 | 2017-08-15 | Apple Inc. | Determining domain salience ranking from ambiguous words in natural speech |
US10289433B2 (en) | 2014-05-30 | 2019-05-14 | Apple Inc. | Domain specific language for encoding assistant dialog |
US9760559B2 (en) | 2014-05-30 | 2017-09-12 | Apple Inc. | Predictive text input |
US9338493B2 (en) | 2014-06-30 | 2016-05-10 | Apple Inc. | Intelligent automated assistant for TV user interactions |
US10659851B2 (en) | 2014-06-30 | 2020-05-19 | Apple Inc. | Real-time digital assistant knowledge updates |
US10446141B2 (en) | 2014-08-28 | 2019-10-15 | Apple Inc. | Automatic speech recognition based on user feedback |
US9818400B2 (en) | 2014-09-11 | 2017-11-14 | Apple Inc. | Method and apparatus for discovering trending terms in speech requests |
US10789041B2 (en) | 2014-09-12 | 2020-09-29 | Apple Inc. | Dynamic thresholds for always listening speech trigger |
SG11201702029PA (en) * | 2014-09-14 | 2017-04-27 | Speaktoit Inc | Platform for creating customizable dialog system engines |
WO2016044321A1 (en) | 2014-09-16 | 2016-03-24 | Min Tang | Integration of domain information into state transitions of a finite state transducer for natural language processing |
CN107003996A (en) | 2014-09-16 | 2017-08-01 | 声钰科技 | VCommerce |
US10127911B2 (en) | 2014-09-30 | 2018-11-13 | Apple Inc. | Speaker identification and unsupervised speaker adaptation techniques |
US9886432B2 (en) | 2014-09-30 | 2018-02-06 | Apple Inc. | Parsimonious handling of word inflection via categorical stem + suffix N-gram language models |
US10074360B2 (en) | 2014-09-30 | 2018-09-11 | Apple Inc. | Providing an indication of the suitability of speech recognition |
US9646609B2 (en) | 2014-09-30 | 2017-05-09 | Apple Inc. | Caching apparatus for serving phonetic pronunciations |
US9668121B2 (en) | 2014-09-30 | 2017-05-30 | Apple Inc. | Social reminders |
CN107003999B (en) | 2014-10-15 | 2020-08-21 | 声钰科技 | System and method for subsequent response to a user's prior natural language input |
US10431214B2 (en) | 2014-11-26 | 2019-10-01 | Voicebox Technologies Corporation | System and method of determining a domain and/or an action related to a natural language input |
US10614799B2 (en) | 2014-11-26 | 2020-04-07 | Voicebox Technologies Corporation | System and method of providing intent predictions for an utterance prior to a system detection of an end of the utterance |
US10552013B2 (en) | 2014-12-02 | 2020-02-04 | Apple Inc. | Data detection |
US9711141B2 (en) | 2014-12-09 | 2017-07-18 | Apple Inc. | Disambiguating heteronyms in speech synthesis |
US9865280B2 (en) | 2015-03-06 | 2018-01-09 | Apple Inc. | Structured dictation using intelligent automated assistants |
US10152299B2 (en) | 2015-03-06 | 2018-12-11 | Apple Inc. | Reducing response latency of intelligent automated assistants |
US9886953B2 (en) | 2015-03-08 | 2018-02-06 | Apple Inc. | Virtual assistant activation |
US10567477B2 (en) | 2015-03-08 | 2020-02-18 | Apple Inc. | Virtual assistant continuity |
US9721566B2 (en) | 2015-03-08 | 2017-08-01 | Apple Inc. | Competing devices responding to voice triggers |
US9899019B2 (en) | 2015-03-18 | 2018-02-20 | Apple Inc. | Systems and methods for structured stem and suffix language models |
US9842105B2 (en) | 2015-04-16 | 2017-12-12 | Apple Inc. | Parsimonious continuous-space phrase representations for natural language processing |
US10083688B2 (en) | 2015-05-27 | 2018-09-25 | Apple Inc. | Device voice control for selecting a displayed affordance |
US10127220B2 (en) | 2015-06-04 | 2018-11-13 | Apple Inc. | Language identification from short strings |
US10101822B2 (en) | 2015-06-05 | 2018-10-16 | Apple Inc. | Language input correction |
US9578173B2 (en) | 2015-06-05 | 2017-02-21 | Apple Inc. | Virtual assistant aided communication with 3rd party service in a communication session |
US10255907B2 (en) | 2015-06-07 | 2019-04-09 | Apple Inc. | Automatic accent detection using acoustic models |
US11025565B2 (en) | 2015-06-07 | 2021-06-01 | Apple Inc. | Personalized prediction of responses for instant messaging |
US10186254B2 (en) | 2015-06-07 | 2019-01-22 | Apple Inc. | Context-based endpoint detection |
US10747498B2 (en) | 2015-09-08 | 2020-08-18 | Apple Inc. | Zero latency digital assistant |
US10671428B2 (en) | 2015-09-08 | 2020-06-02 | Apple Inc. | Distributed personal assistant |
US9697820B2 (en) | 2015-09-24 | 2017-07-04 | Apple Inc. | Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks |
US11010550B2 (en) | 2015-09-29 | 2021-05-18 | Apple Inc. | Unified language modeling framework for word prediction, auto-completion and auto-correction |
US10366158B2 (en) | 2015-09-29 | 2019-07-30 | Apple Inc. | Efficient word encoding for recurrent neural network language models |
US11587559B2 (en) | 2015-09-30 | 2023-02-21 | Apple Inc. | Intelligent device identification |
US10691473B2 (en) | 2015-11-06 | 2020-06-23 | Apple Inc. | Intelligent automated assistant in a messaging environment |
US10049668B2 (en) | 2015-12-02 | 2018-08-14 | Apple Inc. | Applying neural network language models to weighted finite state transducers for automatic speech recognition |
US10223066B2 (en) | 2015-12-23 | 2019-03-05 | Apple Inc. | Proactive assistance based on dialog communication between devices |
US10446143B2 (en) | 2016-03-14 | 2019-10-15 | Apple Inc. | Identification of voice inputs providing credentials |
US9934775B2 (en) | 2016-05-26 | 2018-04-03 | Apple Inc. | Unit-selection text-to-speech synthesis based on predicted concatenation parameters |
US9972304B2 (en) | 2016-06-03 | 2018-05-15 | Apple Inc. | Privacy preserving distributed evaluation framework for embedded personalized systems |
US10249300B2 (en) | 2016-06-06 | 2019-04-02 | Apple Inc. | Intelligent list reading |
US10049663B2 (en) | 2016-06-08 | 2018-08-14 | Apple, Inc. | Intelligent automated assistant for media exploration |
DK179309B1 (en) | 2016-06-09 | 2018-04-23 | Apple Inc | Intelligent automated assistant in a home environment |
US10490187B2 (en) | 2016-06-10 | 2019-11-26 | Apple Inc. | Digital assistant providing automated status report |
US10586535B2 (en) | 2016-06-10 | 2020-03-10 | Apple Inc. | Intelligent digital assistant in a multi-tasking environment |
US10192552B2 (en) | 2016-06-10 | 2019-01-29 | Apple Inc. | Digital assistant providing whispered speech |
US10509862B2 (en) | 2016-06-10 | 2019-12-17 | Apple Inc. | Dynamic phrase expansion of language input |
US10067938B2 (en) | 2016-06-10 | 2018-09-04 | Apple Inc. | Multilingual word prediction |
DK179049B1 (en) | 2016-06-11 | 2017-09-18 | Apple Inc | Data driven natural language event detection and classification |
DK201670540A1 (en) | 2016-06-11 | 2018-01-08 | Apple Inc | Application integration with a digital assistant |
DK179343B1 (en) | 2016-06-11 | 2018-05-14 | Apple Inc | Intelligent task discovery |
DK179415B1 (en) | 2016-06-11 | 2018-06-14 | Apple Inc | Intelligent device arbitration and control |
US10474439B2 (en) | 2016-06-16 | 2019-11-12 | Microsoft Technology Licensing, Llc | Systems and methods for building conversational understanding systems |
WO2018023106A1 (en) | 2016-07-29 | 2018-02-01 | Erik SWART | System and method of disambiguating natural language processing requests |
US10474753B2 (en) | 2016-09-07 | 2019-11-12 | Apple Inc. | Language identification using recurrent neural networks |
US10043516B2 (en) | 2016-09-23 | 2018-08-07 | Apple Inc. | Intelligent automated assistant |
US10057746B1 (en) | 2016-11-16 | 2018-08-21 | Wideorbit, Inc. | Method and system for detecting a user device in an environment associated with a content presentation system presenting content |
US11281993B2 (en) | 2016-12-05 | 2022-03-22 | Apple Inc. | Model and ensemble compression for metric learning |
US10593346B2 (en) | 2016-12-22 | 2020-03-17 | Apple Inc. | Rank-reduced token representation for automatic speech recognition |
US11204787B2 (en) | 2017-01-09 | 2021-12-21 | Apple Inc. | Application integration with a digital assistant |
US10417266B2 (en) | 2017-05-09 | 2019-09-17 | Apple Inc. | Context-aware ranking of intelligent response suggestions |
DK201770383A1 (en) | 2017-05-09 | 2018-12-14 | Apple Inc. | User interface for correcting recognition errors |
US10726832B2 (en) | 2017-05-11 | 2020-07-28 | Apple Inc. | Maintaining privacy of personal information |
US10395654B2 (en) | 2017-05-11 | 2019-08-27 | Apple Inc. | Text normalization based on a data-driven learning network |
DK201770439A1 (en) | 2017-05-11 | 2018-12-13 | Apple Inc. | Offline personal assistant |
DK179496B1 (en) | 2017-05-12 | 2019-01-15 | Apple Inc. | USER-SPECIFIC Acoustic Models |
DK179745B1 (en) | 2017-05-12 | 2019-05-01 | Apple Inc. | SYNCHRONIZATION AND TASK DELEGATION OF A DIGITAL ASSISTANT |
DK201770429A1 (en) | 2017-05-12 | 2018-12-14 | Apple Inc. | Low-latency intelligent automated assistant |
US11301477B2 (en) | 2017-05-12 | 2022-04-12 | Apple Inc. | Feedback analysis of a digital assistant |
DK201770431A1 (en) | 2017-05-15 | 2018-12-20 | Apple Inc. | Optimizing dialogue policy decisions for digital assistants using implicit feedback |
DK201770432A1 (en) | 2017-05-15 | 2018-12-21 | Apple Inc. | Hierarchical belief states for digital assistants |
DK179560B1 (en) | 2017-05-16 | 2019-02-18 | Apple Inc. | Far-field extension for digital assistant services |
US10303715B2 (en) | 2017-05-16 | 2019-05-28 | Apple Inc. | Intelligent automated assistant for media exploration |
US10403278B2 (en) | 2017-05-16 | 2019-09-03 | Apple Inc. | Methods and systems for phonetic matching in digital assistant services |
US10311144B2 (en) | 2017-05-16 | 2019-06-04 | Apple Inc. | Emoji word sense disambiguation |
US10657328B2 (en) | 2017-06-02 | 2020-05-19 | Apple Inc. | Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling |
US10515625B1 (en) | 2017-08-31 | 2019-12-24 | Amazon Technologies, Inc. | Multi-modal natural language processing |
US10445429B2 (en) | 2017-09-21 | 2019-10-15 | Apple Inc. | Natural language understanding using vocabularies with compressed serialized tries |
US10755051B2 (en) | 2017-09-29 | 2020-08-25 | Apple Inc. | Rule-based natural language processing |
US11869039B1 (en) | 2017-11-13 | 2024-01-09 | Wideorbit Llc | Detecting gestures associated with content displayed in a physical environment |
US10636424B2 (en) | 2017-11-30 | 2020-04-28 | Apple Inc. | Multi-turn canned dialog |
US10733982B2 (en) | 2018-01-08 | 2020-08-04 | Apple Inc. | Multi-directional dialog |
US10839160B2 (en) * | 2018-01-19 | 2020-11-17 | International Business Machines Corporation | Ontology-based automatic bootstrapping of state-based dialog systems |
US11043230B1 (en) * | 2018-01-25 | 2021-06-22 | Wideorbit Inc. | Targeted content based on user reactions |
US10733375B2 (en) | 2018-01-31 | 2020-08-04 | Apple Inc. | Knowledge-based framework for improving natural language understanding |
US10789959B2 (en) | 2018-03-02 | 2020-09-29 | Apple Inc. | Training speaker recognition models for digital assistants |
US10592604B2 (en) | 2018-03-12 | 2020-03-17 | Apple Inc. | Inverse text normalization for automatic speech recognition |
US10818288B2 (en) | 2018-03-26 | 2020-10-27 | Apple Inc. | Natural assistant interaction |
US10909331B2 (en) | 2018-03-30 | 2021-02-02 | Apple Inc. | Implicit identification of translation payload with neural machine translation |
US10928918B2 (en) | 2018-05-07 | 2021-02-23 | Apple Inc. | Raise to speak |
US11145294B2 (en) | 2018-05-07 | 2021-10-12 | Apple Inc. | Intelligent automated assistant for delivering content from user experiences |
US10984780B2 (en) | 2018-05-21 | 2021-04-20 | Apple Inc. | Global semantic word embeddings using bi-directional recurrent neural networks |
US11386266B2 (en) | 2018-06-01 | 2022-07-12 | Apple Inc. | Text correction |
DK179822B1 (en) | 2018-06-01 | 2019-07-12 | Apple Inc. | Voice interaction at a primary device to access call functionality of a companion device |
DK180639B1 (en) | 2018-06-01 | 2021-11-04 | Apple Inc | DISABILITY OF ATTENTION-ATTENTIVE VIRTUAL ASSISTANT |
US10892996B2 (en) | 2018-06-01 | 2021-01-12 | Apple Inc. | Variable latency device coordination |
DK201870355A1 (en) | 2018-06-01 | 2019-12-16 | Apple Inc. | Virtual assistant operation in multi-device environments |
US10496705B1 (en) | 2018-06-03 | 2019-12-03 | Apple Inc. | Accelerated task performance |
US11386338B2 (en) | 2018-07-05 | 2022-07-12 | International Business Machines Corporation | Integrating multiple domain problem solving in a dialog system for a user |
CN110737762A (en) * | 2019-10-09 | 2020-01-31 | 尹曦 | old people personal information assistant system based on voice interaction |
US11176942B2 (en) * | 2019-11-26 | 2021-11-16 | Vui, Inc. | Multi-modal conversational agent platform |
EP4089569A1 (en) * | 2021-05-12 | 2022-11-16 | PolyAI Limited | A dialogue system and a dialogue method |
US11430446B1 (en) | 2021-08-12 | 2022-08-30 | PolyAI Limited | Dialogue system and a dialogue method |
US12056457B2 (en) * | 2022-03-22 | 2024-08-06 | Charles University, Faculty Of Mathematics And Physics | Computer-implemented method of real time speech translation and a computer system for carrying out the method |
Citations (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5597312A (en) * | 1994-05-04 | 1997-01-28 | U S West Technologies, Inc. | Intelligent tutoring method and system |
US5699456A (en) * | 1994-01-21 | 1997-12-16 | Lucent Technologies Inc. | Large vocabulary connected speech recognition system and method of language representation using evolutional grammar to represent context free grammars |
US6738518B1 (en) * | 2000-05-12 | 2004-05-18 | Xerox Corporation | Document image decoding using text line column-based heuristic scoring |
US20050165607A1 (en) * | 2004-01-22 | 2005-07-28 | At&T Corp. | System and method to disambiguate and clarify user intention in a spoken dialog system |
US7024350B2 (en) * | 2000-07-20 | 2006-04-04 | Microsoft Corporation | Compact easily parseable binary format for a context-free grammer |
US7397905B1 (en) * | 2004-08-13 | 2008-07-08 | Edify Corporation | Interactive voice response (IVR) system providing dynamic resolution of data |
US7412393B1 (en) * | 2004-03-01 | 2008-08-12 | At&T Corp. | Method for developing a dialog manager using modular spoken-dialog components |
US7421393B1 (en) * | 2004-03-01 | 2008-09-02 | At&T Corp. | System for developing a dialog manager using modular spoken-dialog components |
US7430510B1 (en) * | 2004-03-01 | 2008-09-30 | At&T Corp. | System and method of using modular spoken-dialog components |
US7603651B2 (en) * | 2000-11-21 | 2009-10-13 | Filip De Brabander | Language modelling system and a fast parsing method |
US7720684B2 (en) * | 2005-04-29 | 2010-05-18 | Nuance Communications, Inc. | Method, apparatus, and computer program product for one-step correction of voice interaction |
US7805305B2 (en) * | 2006-10-12 | 2010-09-28 | Nuance Communications, Inc. | Enhancement to Viterbi speech processing algorithm for hybrid speech models that conserves memory |
Family Cites Families (49)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS5629292A (en) * | 1979-08-17 | 1981-03-24 | Nippon Electric Co | Continuous voice identifier |
US5268990A (en) * | 1991-01-31 | 1993-12-07 | Sri International | Method for recognizing speech using linguistically-motivated hidden Markov models |
EP0692135B1 (en) * | 1993-03-12 | 2000-08-16 | Sri International | Method and apparatus for voice-interactive language instruction |
US5511003A (en) * | 1993-11-24 | 1996-04-23 | Intel Corporation | Encoding and decoding video signals using spatial filtering |
US5890123A (en) * | 1995-06-05 | 1999-03-30 | Lucent Technologies, Inc. | System and method for voice controlled video screen display |
US5799276A (en) * | 1995-11-07 | 1998-08-25 | Accent Incorporated | Knowledge-based speech recognition system and methods having frame length computed based upon estimated pitch period of vocalic intervals |
US6023697A (en) * | 1997-02-24 | 2000-02-08 | Gte Internetworking Incorporated | Systems and methods for providing user assistance in retrieving data from a relational database |
US6044347A (en) | 1997-08-05 | 2000-03-28 | Lucent Technologies Inc. | Methods and apparatus object-oriented rule-based dialogue management |
US5960384A (en) * | 1997-09-03 | 1999-09-28 | Brash; Douglas E. | Method and device for parsing natural language sentences and other sequential symbolic expressions |
US6134524A (en) * | 1997-10-24 | 2000-10-17 | Nortel Networks Corporation | Method and apparatus to detect and delimit foreground speech |
US6073098A (en) * | 1997-11-21 | 2000-06-06 | At&T Corporation | Method and apparatus for generating deterministic approximate weighted finite-state automata |
US6144938A (en) * | 1998-05-01 | 2000-11-07 | Sun Microsystems, Inc. | Voice user interface with personality |
US6236968B1 (en) | 1998-05-14 | 2001-05-22 | International Business Machines Corporation | Sleep prevention dialog based car system |
US6587822B2 (en) * | 1998-10-06 | 2003-07-01 | Lucent Technologies Inc. | Web-based platform for interactive voice response (IVR) |
US6246981B1 (en) | 1998-11-25 | 2001-06-12 | International Business Machines Corporation | Natural language task-oriented dialog manager and method |
JP4176228B2 (en) | 1999-03-15 | 2008-11-05 | 株式会社東芝 | Natural language dialogue apparatus and natural language dialogue method |
US6314402B1 (en) * | 1999-04-23 | 2001-11-06 | Nuance Communications | Method and apparatus for creating modifiable and combinable speech objects for acquiring information from a speaker in an interactive voice response system |
US6356869B1 (en) * | 1999-04-30 | 2002-03-12 | Nortel Networks Limited | Method and apparatus for discourse management |
TW501046B (en) | 1999-06-11 | 2002-09-01 | Ind Tech Res Inst | A portable dialogue manager |
US6788768B1 (en) * | 1999-09-13 | 2004-09-07 | Microstrategy, Incorporated | System and method for real-time, personalized, dynamic, interactive voice services for book-related information |
US7143042B1 (en) * | 1999-10-04 | 2006-11-28 | Nuance Communications | Tool for graphically defining dialog flows and for establishing operational links between speech applications and hypermedia content in an interactive voice response environment |
US6587818B2 (en) | 1999-10-28 | 2003-07-01 | International Business Machines Corporation | System and method for resolving decoding ambiguity via dialog |
US6513009B1 (en) | 1999-12-14 | 2003-01-28 | International Business Machines Corporation | Scalable low resource dialog manager |
US6453474B2 (en) | 2000-01-27 | 2002-09-24 | Hillerich & Bradsby Co. | Hockey goaltender catch glove |
US7167830B2 (en) | 2000-03-10 | 2007-01-23 | Entrieva, Inc. | Multimodal information services |
US20020001370A1 (en) | 2000-06-05 | 2002-01-03 | Walker David L. | Voice portal platform |
US7334050B2 (en) * | 2000-06-07 | 2008-02-19 | Nvidia International, Inc. | Voice applications and voice-based interface |
GB0025331D0 (en) * | 2000-10-16 | 2000-11-29 | Canon Kk | Control apparatus |
US6728679B1 (en) | 2000-10-30 | 2004-04-27 | Koninklijke Philips Electronics N.V. | Self-updating user interface/entertainment device that simulates personal interaction |
US7158935B1 (en) * | 2000-11-15 | 2007-01-02 | At&T Corp. | Method and system for predicting problematic situations in a automated dialog |
US7487440B2 (en) * | 2000-12-04 | 2009-02-03 | International Business Machines Corporation | Reusable voiceXML dialog components, subdialogs and beans |
US6961694B2 (en) * | 2001-01-22 | 2005-11-01 | Microsoft Corporation | Method and apparatus for reducing latency in speech-based applications |
US6751591B1 (en) * | 2001-01-22 | 2004-06-15 | At&T Corp. | Method and system for predicting understanding errors in a task classification system |
US6964023B2 (en) * | 2001-02-05 | 2005-11-08 | International Business Machines Corporation | System and method for multi-modal focus detection, referential ambiguity resolution and mood classification using multi-modal input |
EP1255190A1 (en) * | 2001-05-04 | 2002-11-06 | Microsoft Corporation | Interface control |
DE60136052D1 (en) * | 2001-05-04 | 2008-11-20 | Microsoft Corp | Interface control |
US6839896B2 (en) * | 2001-06-29 | 2005-01-04 | International Business Machines Corporation | System and method for providing dialog management and arbitration in a multi-modal environment |
US7167832B2 (en) * | 2001-10-15 | 2007-01-23 | At&T Corp. | Method for dialog management |
US7139717B1 (en) * | 2001-10-15 | 2006-11-21 | At&T Corp. | System for dialog management |
US7711570B2 (en) * | 2001-10-21 | 2010-05-04 | Microsoft Corporation | Application abstraction with dialog purpose |
US7174300B2 (en) * | 2001-12-11 | 2007-02-06 | Lockheed Martin Corporation | Dialog processing method and apparatus for uninhabited air vehicles |
US7260530B2 (en) | 2002-02-15 | 2007-08-21 | Bevocal, Inc. | Enhanced go-back feature system and method for use in a voice portal |
US7197460B1 (en) * | 2002-04-23 | 2007-03-27 | At&T Corp. | System for handling frequently asked questions in a natural language dialog service |
US7177816B2 (en) * | 2002-07-05 | 2007-02-13 | At&T Corp. | System and method of handling problematic input during context-sensitive help for multi-modal dialog systems |
US7177815B2 (en) | 2002-07-05 | 2007-02-13 | At&T Corp. | System and method of context-sensitive help for multi-modal dialog systems |
JP2004271764A (en) * | 2003-03-06 | 2004-09-30 | Nagoya Industrial Science Research Inst | Finite state transducer generator, program, recording medium, generation method, and gradual syntax analysis system |
US7552055B2 (en) * | 2004-01-10 | 2009-06-23 | Microsoft Corporation | Dialog component re-use in recognition systems |
US20050246174A1 (en) * | 2004-04-28 | 2005-11-03 | Degolia Richard C | Method and system for presenting dynamic commercial content to clients interacting with a voice extensible markup language system |
US8520808B2 (en) * | 2008-10-08 | 2013-08-27 | Synchronoss Technologies | System and method for robust evaluation of the user experience in automated spoken dialog systems |
-
2004
- 2004-03-01 US US10/790,495 patent/US7421393B1/en active Active
-
2008
- 2008-08-29 US US12/201,423 patent/US8473299B2/en active Active
-
2013
- 2013-06-25 US US13/926,366 patent/US8725517B2/en not_active Expired - Lifetime
-
2014
- 2014-04-25 US US14/261,549 patent/US9257116B2/en not_active Expired - Lifetime
-
2016
- 2016-02-02 US US15/013,040 patent/US20160154788A1/en not_active Abandoned
Patent Citations (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5699456A (en) * | 1994-01-21 | 1997-12-16 | Lucent Technologies Inc. | Large vocabulary connected speech recognition system and method of language representation using evolutional grammar to represent context free grammars |
US5597312A (en) * | 1994-05-04 | 1997-01-28 | U S West Technologies, Inc. | Intelligent tutoring method and system |
US6738518B1 (en) * | 2000-05-12 | 2004-05-18 | Xerox Corporation | Document image decoding using text line column-based heuristic scoring |
US7024350B2 (en) * | 2000-07-20 | 2006-04-04 | Microsoft Corporation | Compact easily parseable binary format for a context-free grammer |
US7603651B2 (en) * | 2000-11-21 | 2009-10-13 | Filip De Brabander | Language modelling system and a fast parsing method |
US20050165607A1 (en) * | 2004-01-22 | 2005-07-28 | At&T Corp. | System and method to disambiguate and clarify user intention in a spoken dialog system |
US7412393B1 (en) * | 2004-03-01 | 2008-08-12 | At&T Corp. | Method for developing a dialog manager using modular spoken-dialog components |
US7421393B1 (en) * | 2004-03-01 | 2008-09-02 | At&T Corp. | System for developing a dialog manager using modular spoken-dialog components |
US7430510B1 (en) * | 2004-03-01 | 2008-09-30 | At&T Corp. | System and method of using modular spoken-dialog components |
US20080306743A1 (en) * | 2004-03-01 | 2008-12-11 | At&T Corp. | System and method of using modular spoken-dialog components |
US8473299B2 (en) * | 2004-03-01 | 2013-06-25 | At&T Intellectual Property I, L.P. | System and dialog manager developed using modular spoken-dialog components |
US8630859B2 (en) * | 2004-03-01 | 2014-01-14 | At&T Intellectual Property Ii, L.P. | Method for developing a dialog manager using modular spoken-dialog components |
US7397905B1 (en) * | 2004-08-13 | 2008-07-08 | Edify Corporation | Interactive voice response (IVR) system providing dynamic resolution of data |
US7720684B2 (en) * | 2005-04-29 | 2010-05-18 | Nuance Communications, Inc. | Method, apparatus, and computer program product for one-step correction of voice interaction |
US7805305B2 (en) * | 2006-10-12 | 2010-09-28 | Nuance Communications, Inc. | Enhancement to Viterbi speech processing algorithm for hybrid speech models that conserves memory |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9257116B2 (en) * | 2003-05-15 | 2016-02-09 | At&T Intellectual Property Ii, L.P. | System and dialog manager developed using modular spoken-dialog components |
US10957310B1 (en) | 2012-07-23 | 2021-03-23 | Soundhound, Inc. | Integrated programming framework for speech and text understanding with meaning parsing |
US10996931B1 (en) | 2012-07-23 | 2021-05-04 | Soundhound, Inc. | Integrated programming framework for speech and text understanding with block and statement structure |
US11776533B2 (en) | 2012-07-23 | 2023-10-03 | Soundhound, Inc. | Building a natural language understanding application using a received electronic record containing programming code including an interpret-block, an interpret-statement, a pattern expression and an action statement |
US11295730B1 (en) | 2014-02-27 | 2022-04-05 | Soundhound, Inc. | Using phonetic variants in a local context to improve natural language understanding |
Also Published As
Publication number | Publication date |
---|---|
US9257116B2 (en) | 2016-02-09 |
US7421393B1 (en) | 2008-09-02 |
US20080319763A1 (en) | 2008-12-25 |
US8473299B2 (en) | 2013-06-25 |
US20160154788A1 (en) | 2016-06-02 |
US20130289990A1 (en) | 2013-10-31 |
US8725517B2 (en) | 2014-05-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9257116B2 (en) | System and dialog manager developed using modular spoken-dialog components | |
US8630859B2 (en) | Method for developing a dialog manager using modular spoken-dialog components | |
US7778836B2 (en) | System and method of using modular spoken-dialog components | |
US7389213B2 (en) | Dialogue flow interpreter development tool | |
US7143040B2 (en) | Interactive dialogues | |
Pieraccini et al. | Where do we go from here? Research and commercial spoken dialogue systems | |
US7634259B2 (en) | Applications server and method | |
Young et al. | The design and implementation of dialogue control in voice operated database inquiry systems | |
US20080098353A1 (en) | System and Method to Graphically Facilitate Speech Enabled User Interfaces | |
CA2535496C (en) | Development framework for mixing semantics-driven and state driven dialog | |
JP2007122747A (en) | Dialogue flow interpreter | |
WO2008008328A2 (en) | Authoring and running speech related applications | |
US20020169618A1 (en) | Providing help information in a speech dialog system | |
US20060031853A1 (en) | System and method for optimizing processing speed to run multiple dialogs between multiple users and a virtual agent | |
US20040217986A1 (en) | Enhanced graphical development environment for controlling mixed initiative applications | |
Di Fabbrizio et al. | Florence: a dialogue manager framework for spoken dialogue systems. | |
CA2411888C (en) | Interactive dialogues | |
Hanrieder | Integration of a mixed-initiative dialogue manager into commercial IVR platforms | |
WO2005038775A1 (en) | System, method, and programming language for developing and running dialogs between a user and a virtual agent | |
Dybkjær et al. | Modeling complex spoken dialog | |
Lewin et al. | Siridus system architecture and interface report (baseline) | |
Francisco | Creating an Agent for Amazon’s Alexa | |
Berman et al. | Implemented SIRIDUS system architecture (Baseline) | |
Andreani et al. | Florence XML (FXML) |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: AT&T CORP., NEW YORK Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:DI FABBRIZIO, GIUSEPPE;LEWIS, CHARLES ALFRED;SIGNING DATES FROM 20040226 TO 20040227;REEL/FRAME:035098/0442 |
|
AS | Assignment |
Owner name: AT&T PROPERTIES, LLC, NEVADA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:AT&T CORP.;REEL/FRAME:035135/0404 Effective date: 20150303 Owner name: AT&T INTELLECTUAL PROPERTY II, L.P., GEORGIA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:AT&T PROPERTIES, LLC;REEL/FRAME:035135/0903 Effective date: 20150303 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
AS | Assignment |
Owner name: NUANCE COMMUNICATIONS, INC., MASSACHUSETTS Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:AT&T INTELLECTUAL PROPERTY II, L.P.;REEL/FRAME:041512/0608 Effective date: 20161214 |
|
MAFP | Maintenance fee payment |
Free format text: PAYMENT OF MAINTENANCE FEE, 4TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1551); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY Year of fee payment: 4 |
|
MAFP | Maintenance fee payment |
Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1552); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY Year of fee payment: 8 |
|
AS | Assignment |
Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:NUANCE COMMUNICATIONS, INC.;REEL/FRAME:065490/0151 Effective date: 20230920 |
|
AS | Assignment |
Owner name: MICROSOFT TECHNOLOGY LICENSING, LLC, WASHINGTON Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:NUANCE COMMUNICATIONS, INC.;REEL/FRAME:065532/0152 Effective date: 20230920 |